OffSec's new framework hub shows security leaders what their teams can do and how to prove it.
The post OffSec Aligns Its Cyber Workforce Development Programs to Global Workforce Frameworks appeared first on OffSec.
Learn all about scoring updates to the OSCP exam that are starting on December 1, 2026.
The post OSCP+ Scoring Update: What You Need to Know appeared first on OffSec.
Companies like Google and Microsoft are finding much bigger numbers of vulnerabilities in their own products as a result of AI. But the same technology is leading to public reporting programs becoming overwhelmed by the mass submission of speculative, duplicated, or hallucinated findings.
Now, Google’s announced it has temporarily stopped accepting submissions to its open source bug bounty program, OSS VRP.
“Why is this happening? This pause is due to a significant rise in automated submissions, the vast majority of which are not valid.”
We’ve seen this happen before. In early 2026, curl ended its HackerOne bounty program after low-quality, often AI-generated submissions overwhelmed its small security team.
Intel also launched a new bug bounty program on Intigriti but there are no longer bounties available, reportedly in order to stop a flood of AI generated reports.
Bounties can be an incentive for mass-submitting behavior when generative AI lowers the cost of producing polished-looking submissions. So, it’s understandable that companies want to limit the number of incoming reports.
If most automated submissions are invalid, a temporary pause prevents Google engineers and open-source maintainers from spending disproportionate time disproving reports rather than fixing real issues.
A pause gives Google the time and chance to introduce better controls, such as mandatory proof-of-concept requirements, evidence thresholds, and rate limits without letting the current queue keep growing.
On the other hand, it may discourage legitimate researchers and make it harder for them to submit actual issues they’ve found.
It is hard to draw a line of what you will accept, because an AI-assisted report can be valid, just like a low-quality report is not necessarily AI-generated.
And as companies like Google and Microsoft have proven, AI assisted vulnerability discovery can also support real vulnerability discovery if it is coupled with validation, deduplication, and proof.
If we have learned anything it is that AI is not “breaking” vulnerability disclosure. It is exposing an older weakness in disclosure economics: the cost of filing a plausible report has fallen sharply, while the cost of proving or disproving it remains human-intensive.
The solution seems obvious. Let AI handle the submissions and only hand over those it can validate to the engineering teams. This will definitely frustrate some bug bounty hunters, because it will be like convincing a chatbot that you have a valid point and want to “talk to a human,” but hopefully it will bring down the number of less serious bug bounty hunters and create more room for those who know what they are doing.
Google has only promised an update in Q1 2027, so any redesign details would be speculative, but we do hope they find a way for responsible bug hunters to submit their findings.
From reporting threats to removing them.
Cybersecurity risks should never spread beyond a headline. Keep threats off your devices by downloading Malwarebytes today.
Companies like Google and Microsoft are finding much bigger numbers of vulnerabilities in their own products as a result of AI. But the same technology is leading to public reporting programs becoming overwhelmed by the mass submission of speculative, duplicated, or hallucinated findings.
Now, Google’s announced it has temporarily stopped accepting submissions to its open source bug bounty program, OSS VRP.
“Why is this happening? This pause is due to a significant rise in automated submissions, the vast majority of which are not valid.”
We’ve seen this happen before. In early 2026, curl ended its HackerOne bounty program after low-quality, often AI-generated submissions overwhelmed its small security team.
Intel also launched a new bug bounty program on Intigriti but there are no longer bounties available, reportedly in order to stop a flood of AI generated reports.
Bounties can be an incentive for mass-submitting behavior when generative AI lowers the cost of producing polished-looking submissions. So, it’s understandable that companies want to limit the number of incoming reports.
If most automated submissions are invalid, a temporary pause prevents Google engineers and open-source maintainers from spending disproportionate time disproving reports rather than fixing real issues.
A pause gives Google the time and chance to introduce better controls, such as mandatory proof-of-concept requirements, evidence thresholds, and rate limits without letting the current queue keep growing.
On the other hand, it may discourage legitimate researchers and make it harder for them to submit actual issues they’ve found.
It is hard to draw a line of what you will accept, because an AI-assisted report can be valid, just like a low-quality report is not necessarily AI-generated.
And as companies like Google and Microsoft have proven, AI assisted vulnerability discovery can also support real vulnerability discovery if it is coupled with validation, deduplication, and proof.
If we have learned anything it is that AI is not “breaking” vulnerability disclosure. It is exposing an older weakness in disclosure economics: the cost of filing a plausible report has fallen sharply, while the cost of proving or disproving it remains human-intensive.
The solution seems obvious. Let AI handle the submissions and only hand over those it can validate to the engineering teams. This will definitely frustrate some bug bounty hunters, because it will be like convincing a chatbot that you have a valid point and want to “talk to a human,” but hopefully it will bring down the number of less serious bug bounty hunters and create more room for those who know what they are doing.
Google has only promised an update in Q1 2027, so any redesign details would be speculative, but we do hope they find a way for responsible bug hunters to submit their findings.
From reporting threats to removing them.
Cybersecurity risks should never spread beyond a headline. Keep threats off your devices by downloading Malwarebytes today.
Automated license plate readers (ALPRs) are cameras that photograph passing vehicles, read their number plates, and typically log the time, location, and vehicle details. On their own, the images might be used to find a stolen car or locate a suspect.
But lately there have been a lot of concerns raised about the way they are used. The main worry is caused by what happens when many cameras feed data into a shared, searchable network: it can create a detailed record of where ordinary people travel.
Some agencies have already taken it upon themselves to act on these concerns, as well as those around inaccuracy. Data errors can have serious consequences. At a recent Senate hearing, Florida resident Lindsey Isaacs described being arrested and held for 13 days after data from an AI-enabled plate-reader system incorrectly implicated her in a fatal car crash.
As a result of all this, US lawmakers from both major political parties have introduced proposals aimed at restricting automatic license plate reader networks.
Most of the reasons brought up are about Flock Safety, one of the largest suppliers of these systems in the United States, but they would apply more broadly to other ALPR vendors as well.
Flock says it deploys only 120,000 cameras operating across the country, while a researcher cited by the Senate described a much larger network of connected devices and cameras. The exact size may be disputed, but the central concern is clear: Data from a camera in one location can potentially be searched by an agency elsewhere.
Reportedly, there are two different proposed laws in the making, while Flock says it supports a legal framework for license-plate readers and argues that the technology can improve public safety when it is used with strong oversight and accountability.
The first proposal, the Stop Flock Abuse Act, doesn’t aim to banish ALPR systems outright, it would create rules for how government agencies and vendors can use them.
Among other measures, the bill would require written approval and a record for every search, regular supervisor audits, encryption, and deletion of most vehicle-location data after ten days. It would also prohibit sharing or selling the data to non-governmental third parties, prevent ALPR networks from incorporating facial-recognition technology, and require data to stay in the US.
A second proposal, the Ban Flock Act, takes a much harder line. It would prohibit US federal agencies from using ALPRs or accessing data they collect. It would also withhold federal grant money from state and local governments that use ALPR systems and allow people to sue the federal government if their rights are violated through ALPR deployment.
Both bills are proposals, not enacted laws. In the US system, each would need to pass both the House of Representatives and the Senate in matching form, then be signed by the President.
There is no guarantee either bill will receive a vote, let alone become law. But their introduction shows that ALPR technology is moving from a local procurement issue to a national privacy and civil-liberties debate.
License plate data may seem less sensitive than phone-location data, but a long enough record can reveal a person’s routines, relationships, medical visits, religious activity, or attendance at protests. The debate is therefore not just about cameras on streets to fight crime and find criminals, it is about whether governments and private vendors should be able to build searchable records of everyday movement.
So for consumers, the key question is not only whether a camera is installed on a street or near a business. It is also how long the resulting data is retained, who can search it, whether those searches are logged and reviewed, whether the information can be shared beyond the original agency, and what recourse exists when the system is wrong or abused.
Your name, address, and phone number may already be for sale.
Data brokers collect and sell your personal details to anyone willing to pay. Malwarebytes Personal Data Remover finds them and gets your information removed, then keeps watch so it stays that way.
Automated license plate readers (ALPRs) are cameras that photograph passing vehicles, read their number plates, and typically log the time, location, and vehicle details. On their own, the images might be used to find a stolen car or locate a suspect.
But lately there have been a lot of concerns raised about the way they are used. The main worry is caused by what happens when many cameras feed data into a shared, searchable network: it can create a detailed record of where ordinary people travel.
Some agencies have already taken it upon themselves to act on these concerns, as well as those around inaccuracy. Data errors can have serious consequences. At a recent Senate hearing, Florida resident Lindsey Isaacs described being arrested and held for 13 days after data from an AI-enabled plate-reader system incorrectly implicated her in a fatal car crash.
As a result of all this, US lawmakers from both major political parties have introduced proposals aimed at restricting automatic license plate reader networks.
Most of the reasons brought up are about Flock Safety, one of the largest suppliers of these systems in the United States, but they would apply more broadly to other ALPR vendors as well.
Flock says it deploys only 120,000 cameras operating across the country, while a researcher cited by the Senate described a much larger network of connected devices and cameras. The exact size may be disputed, but the central concern is clear: Data from a camera in one location can potentially be searched by an agency elsewhere.
Reportedly, there are two different proposed laws in the making, while Flock says it supports a legal framework for license-plate readers and argues that the technology can improve public safety when it is used with strong oversight and accountability.
The first proposal, the Stop Flock Abuse Act, doesn’t aim to banish ALPR systems outright, it would create rules for how government agencies and vendors can use them.
Among other measures, the bill would require written approval and a record for every search, regular supervisor audits, encryption, and deletion of most vehicle-location data after ten days. It would also prohibit sharing or selling the data to non-governmental third parties, prevent ALPR networks from incorporating facial-recognition technology, and require data to stay in the US.
A second proposal, the Ban Flock Act, takes a much harder line. It would prohibit US federal agencies from using ALPRs or accessing data they collect. It would also withhold federal grant money from state and local governments that use ALPR systems and allow people to sue the federal government if their rights are violated through ALPR deployment.
Both bills are proposals, not enacted laws. In the US system, each would need to pass both the House of Representatives and the Senate in matching form, then be signed by the President.
There is no guarantee either bill will receive a vote, let alone become law. But their introduction shows that ALPR technology is moving from a local procurement issue to a national privacy and civil-liberties debate.
License plate data may seem less sensitive than phone-location data, but a long enough record can reveal a person’s routines, relationships, medical visits, religious activity, or attendance at protests. The debate is therefore not just about cameras on streets to fight crime and find criminals, it is about whether governments and private vendors should be able to build searchable records of everyday movement.
So for consumers, the key question is not only whether a camera is installed on a street or near a business. It is also how long the resulting data is retained, who can search it, whether those searches are logged and reviewed, whether the information can be shared beyond the original agency, and what recourse exists when the system is wrong or abused.
Your name, address, and phone number may already be for sale.
Data brokers collect and sell your personal details to anyone willing to pay. Malwarebytes Personal Data Remover finds them and gets your information removed, then keeps watch so it stays that way.
Last week on Malwarebytes Labs:
Stay safe!
Scammers know more about you than you think.
Malwarebytes Mobile Security protects you from phishing, scam texts, malicious sites, and more. With real-time AI-powered Scam Guard built right in.
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Stay safe!
Scammers know more about you than you think.
Malwarebytes Mobile Security protects you from phishing, scam texts, malicious sites, and more. With real-time AI-powered Scam Guard built right in.
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In this blog we explore the recently published Forrester Wave: External Threat Intelligence Service Providers, Q3 2026 report which named Flashpoint a Customer Favorite, along with naming the organization a Strong Performer with the highest scores possible in the criteria of: Fraud Intelligence, Executive Protection, and Pricing Flexibility and Transparency.
Table Of ContentsFlashpoint has been named a Customer Favorite and a Strong Performer in The Forrester Wave: External Threat Intelligence Service Providers, Q3 2026.
The Forrester Wave evaluation is a rigorous, data-driven analysis of external threat intelligence service providers across 23 criteria grouped into two categories: Current Offering and Strategy. Alongside its scoring, Forrester incorporates direct customer feedback into its evaluation, and the Forrester report notes that customers “laud Flashpoint’s white-glove approach to addressing diverse customer needs.”
“Customer obsession has been part of Flashpoint’s DNA from day one. When your customers are protecting financial systems, critical infrastructure, national security, and human lives, their mission becomes your mission,” said Josh Lefkowitz, CEO at Flashpoint. “Forrester has built this likeminded customer obsession into how it evaluates vendors, and it’s why being named a Customer Favorite means so much to us. We believe it reflects customers confirming Flashpoint gives them the intelligence, context, and partnership they need to carry out those missions with confidence.”
Flashpoint also received the highest score possible in three criteria: Fraud Intelligence, Executive Protection, and Pricing Flexibility and Transparency. Forrester’s report describes Flashpoint’s Ignite platform as “stand[ing] out for its fraud intelligence capabilities and strong presence across the ecosystem that supports enterprises’ fraud response.” It further describes Flashpoint’s executive protection offering as “structured and comprehensive.”
At the foundation of these capabilities is Flashpoint Primary Source Collection, Flashpoint’s proprietary approach to collecting intelligence directly from the digital environments where threats originate — providing organizations with access to high-value intelligence from open and hard-to-reach sources, enriched by human expertise and scaled by AI. We believe Forrester’s assessment speaks directly to this strength, stating that “Flashpoint is ideal for customers seeking primary source access intelligence, particularly those in the financial industry.” That strength extends well beyond financial services. Organizations across industries rely on Flashpoint to address cyber threats, vulnerability risk, fraud, physical security, geopolitical risk, and brand protection.
The remit of threat intelligence programs continues to expand as the volume and complexity of threats grows, accelerated by AI. Now, a single incident can cross cyber operations, fraud, vulnerability management, executive protection, and physical security, while ownership of those risks may sit across several teams. Threat intelligence solutions need to provide holistic visibility into external activity and enough context to determine what deserves attention.
Flashpoint Ignite gives those teams a common intelligence foundation. In our opinion, the Forrester evaluation reflects that breadth: Flashpoint received the highest score possible in both the Fraud Intelligence and Executive Protection criteria.
For fraud teams, primary-source intelligence can expose compromised credentials, illicit services, access sales, and emerging schemes before they translate into financial loss. For executive protection and physical security teams, it can connect online activity with potential real-world risk to people, facilities, and events.
“Flashpoint saves us over $80 million in fraud losses every year. Their proactive approach and sharp insights are crucial in keeping our financial institution secure. They’re not just a solution; they’re a strategic partner helping us stay ahead of cyber threats.”
SVP Cyber Operations, Large U.S. Financial Institution
Analyst evaluations give buyers a structured view of a complex market. To understand how a threat intelligence platform will perform in practice, security leaders should ask:
“I have used Flashpoint for several years and continue to be impressed with the quality of their services and the thought put into each new offering. Flashpoint is one of the few vendors that has consistently demonstrated a high level of responsiveness and an in-depth understanding of the needs of any threat/fraud/security analyst. Their services cover a wide range of topics from cybersecurity to physical threats, and they are always looking for ways to improve and widen the scope of intelligence they provide.”
Lead Analyst, Cybersecurity
Read The Forrester Wave: External Threat Intelligence Service Providers, Q3 2026 to explore the evaluation and learn more about Flashpoint’s results.
What is The Forrester Wave: External Threat Intelligence Service Providers, Q3 2026?
The Forrester Wave: External Threat Intelligence Service Providers, Q3 2026 evaluates external threat intelligence service providers across their current offering, strategy, and customer feedback to help security leaders assess vendors in the market.
How did Flashpoint perform in Forrester’s latest evaluation of external threat intelligence service providers?
Flashpoint was named a Customer Favorite and a Strong Performer in The Forrester Wave: External Threat Intelligence Service Providers, Q3 2026. Flashpoint received the highest score possible in the Fraud Intelligence, Executive Protection, and Pricing Flexibility and Transparency criteria.
Why was Flashpoint named a Customer Favorite in the Forrester Wave?
Customer Favorite reflects feedback from customers participating in Forrester’s evaluation. Forrester reported that customers “laud Flashpoint’s white-glove approach to addressing diverse customer needs.”
What capabilities was Flashpoint recognized for in the Forrester evaluation?
Forrester described Flashpoint Ignite as standing out for its fraud intelligence capabilities and strong presence across the enterprise fraud response ecosystem, while describing its executive protection offering as “structured and comprehensive.”
What differentiates Flashpoint’s threat intelligence?
Flashpoint is built around Primary Source Collection, its proprietary approach to collecting intelligence directly from the digital environments where threats originate. This gives security teams access to intelligence from open and hard-to-reach sources, enriched by human expertise and scaled by AI. In its assessment, Forrester stated that “Flashpoint is ideal for customers seeking primary source access intelligence, particularly those in the financial industry.” That strength extends across sectors: Flashpoint supports more than 750 customers across industries, helping organizations address security challenges spanning cyber threat intelligence, vulnerability management, fraud, physical security, and geopolitical risk.
What security use cases does Flashpoint support?
Flashpoint supports security teams across cyber threat intelligence, vulnerability intelligence, fraud, executive and physical security, geopolitical risk, and brand protection. These capabilities are delivered through Flashpoint Ignite, allowing organizations to apply a common intelligence foundation across multiple security and risk functions.
Forrester does not endorse any company, product, brand, or service included in its research publications and does not advise any person to select the products or services of any company or brand based on the ratings included in such publications. Information is based on the best available resources. Opinions reflect judgment at the time and are subject to change. This report is part of a broader collection of Forrester resources, including interactive models, frameworks, tools, data, and access to analyst guidance. For more information, read about Forrester’s objectivity here.
The post Flashpoint Named A Customer Favorite in The Forrester Wave™ appeared first on Flashpoint.
Noteworthy stories that might have slipped under the radar: Kiteworks patches over 100 vulnerabilities, Microsoft publishes 2026 Digital Defense Report, AI finds 24 Android app flaws.
The post In Other News: $15K iCloud Spoofing Bugs, AI Policy Experts Phished, Adblocker Spies on AI Chats appeared first on SecurityWeek.
The US government is alerting millions of people that their personal information was stolen during a breach of the Pentagon’s personnel records at the Defense Manpower Data Center (DMDC).
The DMDC is a central US Department of Defense (DoD) organization that manages personnel records, ID credentials, and benefit entitlements for military and civilian staff, veterans, and their families. It maintains over 60 million records for US military and civilian staff and their family members to help determine benefits and entitlements, such as healthcare and retirement.
Reportedly, cybercriminals had access from October 2025 to July 2026. CNN reports that the Pentagon confirmed the breach affects 2.76 million living individuals, potentially including current and former defense personnel or their dependents, and 294,000 deceased individuals.
A notification shared on Reddit states:
“A small number of unauthorized users accessed files on a server containing unencrypted PII.”
PII means personally identifiable information. The attackers gained access by exploiting a security vulnerability in an unspecified file-sharing system. The Pentagon says it has “no indication” of misuse. It hasn’t explained how it reached that conclusion or what it considers misuse, and it doesn’t rule out future misuse of the exposed information.
The exposed data is said to include Social Security numbers, names, dates of birth, sex, race, and service details. Some records also include contact information and occupational specialty.
Besides the risk that this data could help foreign intelligence services track US personnel, affected people face a lasting risk of identity theft. Birth dates cannot be changed, and Social Security numbers can only be changed in limited circumstances.
The Pentagon is offering 12 months of credit monitoring through IDX. If you receive a notification letter, take up the offer and consider a credit freeze with all three major credit bureaus: Equifax, Experian, and TransUnion. A freeze is free and restricts access to your credit report, helping prevent someone from opening new credit accounts in your name.
Other recommendations are:
Let’s face it, an incognito window can only do so much.
Breaches, dark web trading, credit fraud. Malwarebytes Identity Theft Protection monitors for all of it, alerts you fast, and comes with identity theft insurance.
The US government is alerting millions of people that their personal information was stolen during a breach of the Pentagon’s personnel records at the Defense Manpower Data Center (DMDC).
The DMDC is a central US Department of Defense (DoD) organization that manages personnel records, ID credentials, and benefit entitlements for military and civilian staff, veterans, and their families. It maintains over 60 million records for US military and civilian staff and their family members to help determine benefits and entitlements, such as healthcare and retirement.
Reportedly, cybercriminals had access from October 2025 to July 2026. CNN reports that the Pentagon confirmed the breach affects 2.76 million living individuals, potentially including current and former defense personnel or their dependents, and 294,000 deceased individuals.
A notification shared on Reddit states:
“A small number of unauthorized users accessed files on a server containing unencrypted PII.”
PII means personally identifiable information. The attackers gained access by exploiting a security vulnerability in an unspecified file-sharing system. The Pentagon says it has “no indication” of misuse. It hasn’t explained how it reached that conclusion or what it considers misuse, and it doesn’t rule out future misuse of the exposed information.
The exposed data is said to include Social Security numbers, names, dates of birth, sex, race, and service details. Some records also include contact information and occupational specialty.
Besides the risk that this data could help foreign intelligence services track US personnel, affected people face a lasting risk of identity theft. Birth dates cannot be changed, and Social Security numbers can only be changed in limited circumstances.
The Pentagon is offering 12 months of credit monitoring through IDX. If you receive a notification letter, take up the offer and consider a credit freeze with all three major credit bureaus: Equifax, Experian, and TransUnion. A freeze is free and restricts access to your credit report, helping prevent someone from opening new credit accounts in your name.
Other recommendations are:
Let’s face it, an incognito window can only do so much.
Breaches, dark web trading, credit fraud. Malwarebytes Identity Theft Protection monitors for all of it, alerts you fast, and comes with identity theft insurance.
Two separate investigations have raised concerns about betting site DraftKings’ marketing to target problem gamblers, including its use of AI. On September 19, the New York Times reported that the company’s machine learning model targeted people who were more likely to respond to betting promotions by gambling and losing more money.
The model crunched data on each customer, including how often they bet, how much they lost, and what their daily account balances were. According to the report, it used this information to send targeted advertising to lure those people back to the site with promotions. DraftKings uses promotions to entice users into betting more. These offers include profit boosts on winnings.
At news nonprofit ProPublica, journalist Jake Pearson made himself an experimental subject. He spent thousands of dollars betting on the DraftKings app in an experiment to see how the company’s marketing would play out. He reported receiving more promotions as his losses mounted.
After he lost nearly $1,800 betting on basketball in a single evening, DraftKings invited him to a VIP tryout. Full membership followed later.
DraftKings would occasionally send automated messages reminding him to bet responsibly, he said. But he found they were no match for the product design pushing him to do more gambling.
DraftKings denied unfair targeting of gambling customers, arguing instead that its promotions reward engagement rather than losses.
The company’s machine learning model, which former insiders say was developed starting in 2023, replaced a cruder system that crunched basic numbers to report on a user’s behavior.
The newer system dug through data on its own, assessing how much individuals would be likely to lose after receiving promotions. It created an “elasticity” score and used it to identify customers likely to lose more in response to offers, the Times said. This would help the company maximize its return on its promotional spending, said former employee Jayden Butts, who helped develop the system. Butts spoke to the Times as part of an investigation that included interviews with over 40 former employees, along with reviews of Slack communications, internal memos, and betting records.
Other employees attempted to get approval for another model at DraftKings. It would analyze gambling activity in a similar way, but with the opposite goal: to flag users whose gambling was getting out of hand and who were at risk of falling into crisis. According to the data scientists interviewed by the Times, the system showed promise at identifying customers who might need help with compulsive gambling, but DraftKings shut the project down after canceling a demo. Later attempts to develop similar systems within the company also failed.
Digital rights advocates warn that AI enables companies to process more data faster for digital advertising. The Electronic Frontier Foundation says this:
“supercharges the harms of online behavioral advertising.”
It’s particularly damaging when advertising encourages addictive behaviors such as gambling.
And online betting looks set to expand. Companies including DraftKings are now running online casino games in select jurisdictions, while prediction markets that allow people to trade forecasts on specific events are also flourishing.
The statistics on gambling are alarming. The World Health Organization estimates that 1.2% of the world’s adult population has a gambling disorder, and that people betting at harmful levels generate around 60% of gambling losses. People struggling with gambling might find it difficult enough to stay away from gambling venues, but mobile gambling apps with hard-to-ignore push notifications and emails can increase the temptation.
If you gamble, monitor your gambling activity and set limits, avoid chasing losses, give yourself timeouts from gambling, and talk to someone if you’re struggling with compulsive gambling.
In the US, the National Problem Gambling Helpline connects people with support and local resources via phone and online chat. In the UK, GamCare’s National Gambling Helpline provides 24/7 phone support and other resources.
From reporting threats to removing them.
Cybersecurity risks should never spread beyond a headline. Keep threats off your devices by downloading Malwarebytes today.
Two separate investigations have raised concerns about betting site DraftKings’ marketing to target problem gamblers, including its use of AI. On September 19, the New York Times reported that the company’s machine learning model targeted people who were more likely to respond to betting promotions by gambling and losing more money.
The model crunched data on each customer, including how often they bet, how much they lost, and what their daily account balances were. According to the report, it used this information to send targeted advertising to lure those people back to the site with promotions. DraftKings uses promotions to entice users into betting more. These offers include profit boosts on winnings.
At news nonprofit ProPublica, journalist Jake Pearson made himself an experimental subject. He spent thousands of dollars betting on the DraftKings app in an experiment to see how the company’s marketing would play out. He reported receiving more promotions as his losses mounted.
After he lost nearly $1,800 betting on basketball in a single evening, DraftKings invited him to a VIP tryout. Full membership followed later.
DraftKings would occasionally send automated messages reminding him to bet responsibly, he said. But he found they were no match for the product design pushing him to do more gambling.
DraftKings denied unfair targeting of gambling customers, arguing instead that its promotions reward engagement rather than losses.
The company’s machine learning model, which former insiders say was developed starting in 2023, replaced a cruder system that crunched basic numbers to report on a user’s behavior.
The newer system dug through data on its own, assessing how much individuals would be likely to lose after receiving promotions. It created an “elasticity” score and used it to identify customers likely to lose more in response to offers, the Times said. This would help the company maximize its return on its promotional spending, said former employee Jayden Butts, who helped develop the system. Butts spoke to the Times as part of an investigation that included interviews with over 40 former employees, along with reviews of Slack communications, internal memos, and betting records.
Other employees attempted to get approval for another model at DraftKings. It would analyze gambling activity in a similar way, but with the opposite goal: to flag users whose gambling was getting out of hand and who were at risk of falling into crisis. According to the data scientists interviewed by the Times, the system showed promise at identifying customers who might need help with compulsive gambling, but DraftKings shut the project down after canceling a demo. Later attempts to develop similar systems within the company also failed.
Digital rights advocates warn that AI enables companies to process more data faster for digital advertising. The Electronic Frontier Foundation says this:
“supercharges the harms of online behavioral advertising.”
It’s particularly damaging when advertising encourages addictive behaviors such as gambling.
And online betting looks set to expand. Companies including DraftKings are now running online casino games in select jurisdictions, while prediction markets that allow people to trade forecasts on specific events are also flourishing.
The statistics on gambling are alarming. The World Health Organization estimates that 1.2% of the world’s adult population has a gambling disorder, and that people betting at harmful levels generate around 60% of gambling losses. People struggling with gambling might find it difficult enough to stay away from gambling venues, but mobile gambling apps with hard-to-ignore push notifications and emails can increase the temptation.
If you gamble, monitor your gambling activity and set limits, avoid chasing losses, give yourself timeouts from gambling, and talk to someone if you’re struggling with compulsive gambling.
In the US, the National Problem Gambling Helpline connects people with support and local resources via phone and online chat. In the UK, GamCare’s National Gambling Helpline provides 24/7 phone support and other resources.
From reporting threats to removing them.
Cybersecurity risks should never spread beyond a headline. Keep threats off your devices by downloading Malwarebytes today.
London, UK, 1 October 2026 – Heimdal, a global cybersecurity provider, today announced a partnership with Elovade, a European IT security distributor with 250 experts across five countries, to bring its unified security platform to managed service providers (MSPs) across the DACH region: Germany, Austria, and Switzerland. The move extends a relationship that began a […]
The post Heimdal partners with Elovade to bring unified cybersecurity platform to the DACH region appeared first on Heimdal Security Blog.
“Arizona’s court system was targeted by a cyber attack from criminal hackers or their bots.”
This is how the Arizona Supreme Court announced that hackers had attacked the state’s court system and stolen the personal information of “many Arizonans.”
The court says the attack began with a phishing email containing a malicious link that a court employee clicked. The attackers copied sensitive backup files containing records related to protective orders and foster care cases.
The court says it has no evidence, so far, that information about jurors, witnesses, or court employees was included in the copied files. It has not identified the attackers or a motive. It says the case is under investigation with the FBI, and no ransomware group has publicly claimed responsibility.
In an update, the court revealed that the attackers copied more than 150,000 recommendation reports created by Arizona’s Foster Care Review Board. The reports cover current and past cases involving children’s care and protection, dating back to 2010.
Those documents can include information about children, names of involved parties, case materials considered by the board, findings, and recommendations for courts, parents, and the Arizona Department of Child Safety. The court says the reports do not contain contact information such as addresses or telephone numbers.
The copied files were backups stored in a highly compressed format, kept for recovery after ransomware and other destructive incidents.
Information associated with protective orders can raise particularly serious safety and privacy concerns. These orders can protect people from abuse, harassment, or threats. Even where some records are public, combining names, case details, locations, and other sensitive context could create risks for people who are trying to limit their exposure to an abusive or threatening individual.
The court currently says it has no evidence that the information has been shared. As with many breach investigations, however, this can change as investigators determine exactly what was taken and monitor for publication, sale, or misuse of the data.
Arizona has about 8,000 children currently in foster care, according to the court. It is contacting people believed to have been affected.
Let’s face it, an incognito window can only do so much.
Breaches, dark web trading, credit fraud. Malwarebytes Identity Theft Protection monitors for all of it, alerts you fast, and comes with identity theft insurance.
“Arizona’s court system was targeted by a cyber attack from criminal hackers or their bots.”
This is how the Arizona Supreme Court announced that hackers had attacked the state’s court system and stolen the personal information of “many Arizonans.”
The court says the attack began with a phishing email containing a malicious link that a court employee clicked. The attackers copied sensitive backup files containing records related to protective orders and foster care cases.
The court says it has no evidence, so far, that information about jurors, witnesses, or court employees was included in the copied files. It has not identified the attackers or a motive. It says the case is under investigation with the FBI, and no ransomware group has publicly claimed responsibility.
In an update, the court revealed that the attackers copied more than 150,000 recommendation reports created by Arizona’s Foster Care Review Board. The reports cover current and past cases involving children’s care and protection, dating back to 2010.
Those documents can include information about children, names of involved parties, case materials considered by the board, findings, and recommendations for courts, parents, and the Arizona Department of Child Safety. The court says the reports do not contain contact information such as addresses or telephone numbers.
The copied files were backups stored in a highly compressed format, kept for recovery after ransomware and other destructive incidents.
Information associated with protective orders can raise particularly serious safety and privacy concerns. These orders can protect people from abuse, harassment, or threats. Even where some records are public, combining names, case details, locations, and other sensitive context could create risks for people who are trying to limit their exposure to an abusive or threatening individual.
The court currently says it has no evidence that the information has been shared. As with many breach investigations, however, this can change as investigators determine exactly what was taken and monitor for publication, sale, or misuse of the data.
Arizona has about 8,000 children currently in foster care, according to the court. It is contacting people believed to have been affected.
Let’s face it, an incognito window can only do so much.
Breaches, dark web trading, credit fraud. Malwarebytes Identity Theft Protection monitors for all of it, alerts you fast, and comes with identity theft insurance.
A study testing 21 cars from 19 brands and 30 companion apps found connections to advertising and tracking companies, and evidence that some apps shared sensitive personal data.
Modern cars can unlock remotely, route around traffic, stream entertainment, summon roadside help, and cool or heat the cabin before you get in. But those conveniences come with a privacy cost that drivers may struggle to see and are unable to refuse.
We’ve covered cars and privacy a few times before, especially after Mozilla researchers described cars as a “privacy nightmare.”
Texas Attorney General Ken Paxton investigated car manufacturers seeking details of their data collection and sharing practices, and sued General Motors over allegations that it sold customer driving data to third parties.
Researchers from Northeastern University, working with Consumer Reports, tested vehicles from model years 2022 through 2025 and companion apps, observing network traffic while cars were stationary, driven, and used through their apps. The results reinforce an uncomfortable reality: connected vehicles are data-collection platforms on wheels.
The results in a nutshell:
The troubling part is not that a car talks to its manufacturer. After all, a connected vehicle needs some network access for safety alerts, navigation, account functions, and maintenance. The bigger issue is the potential combination of identifiers. A vehicle identification number (VIN) can link a particular vehicle to its owner, while precise location can reveal highly sensitive patterns: where someone sleeps, works, worships, seeks medical care, spends time with friends, or travels. Add an email address or a name, and that information can be easier to connect to the detailed consumer profiles held by advertisers and data brokers.
And that’s before considering the privacy concerns around cameras that monitor drivers’ faces for signs of distraction or impairment.
Consent is a weak safeguard when drivers have to accept extensive terms to use functions advertised as part of the vehicle. Several manufacturers said their connected services were opt-in, but declining can mean losing useful functionality. For example, Consumer Reports noted a Tesla warning that refusing its agreement may result in:
“reduced functionality, serious damage, or inoperability.”
That hardly sounds like freely given, informed consent.
There was one sign that scrutiny can matter: after researchers presented their findings, Honda told Consumer Reports it had directed vendor Amplitude to delete location data it received and stopped sending it going forward. But consumers should not need an academic study to discover who their car or its app is sharing data with.
Especially when Amazon, Google, Meta, and Microsoft—companies that already know plenty about us—were among the leading recipients of the driver data.
Until automakers collect less data and provide clear privacy settings, meaningful opt-outs, and deletion controls, drivers should treat a connected car, and especially its companion app, as another privacy-sensitive device. Review app permissions, turn off optional data-sharing settings, avoid linking unnecessary accounts, and ask manufacturers what data they retain, share, and delete.
Browse like no one’s watching.
Malwarebytes Privacy VPN encrypts your connection and never logs what you do, so the next story you read doesn’t have to feel personal. Try it free →
A study testing 21 cars from 19 brands and 30 companion apps found connections to advertising and tracking companies, and evidence that some apps shared sensitive personal data.
Modern cars can unlock remotely, route around traffic, stream entertainment, summon roadside help, and cool or heat the cabin before you get in. But those conveniences come with a privacy cost that drivers may struggle to see and are unable to refuse.
We’ve covered cars and privacy a few times before, especially after Mozilla researchers described cars as a “privacy nightmare.”
Texas Attorney General Ken Paxton investigated car manufacturers seeking details of their data collection and sharing practices, and sued General Motors over allegations that it sold customer driving data to third parties.
Researchers from Northeastern University, working with Consumer Reports, tested vehicles from model years 2022 through 2025 and companion apps, observing network traffic while cars were stationary, driven, and used through their apps. The results reinforce an uncomfortable reality: connected vehicles are data-collection platforms on wheels.
The results in a nutshell:
The troubling part is not that a car talks to its manufacturer. After all, a connected vehicle needs some network access for safety alerts, navigation, account functions, and maintenance. The bigger issue is the potential combination of identifiers. A vehicle identification number (VIN) can link a particular vehicle to its owner, while precise location can reveal highly sensitive patterns: where someone sleeps, works, worships, seeks medical care, spends time with friends, or travels. Add an email address or a name, and that information can be easier to connect to the detailed consumer profiles held by advertisers and data brokers.
And that’s before considering the privacy concerns around cameras that monitor drivers’ faces for signs of distraction or impairment.
Consent is a weak safeguard when drivers have to accept extensive terms to use functions advertised as part of the vehicle. Several manufacturers said their connected services were opt-in, but declining can mean losing useful functionality. For example, Consumer Reports noted a Tesla warning that refusing its agreement may result in:
“reduced functionality, serious damage, or inoperability.”
That hardly sounds like freely given, informed consent.
There was one sign that scrutiny can matter: after researchers presented their findings, Honda told Consumer Reports it had directed vendor Amplitude to delete location data it received and stopped sending it going forward. But consumers should not need an academic study to discover who their car or its app is sharing data with.
Especially when Amazon, Google, Meta, and Microsoft—companies that already know plenty about us—were among the leading recipients of the driver data.
Until automakers collect less data and provide clear privacy settings, meaningful opt-outs, and deletion controls, drivers should treat a connected car, and especially its companion app, as another privacy-sensitive device. Review app permissions, turn off optional data-sharing settings, avoid linking unnecessary accounts, and ask manufacturers what data they retain, share, and delete.
Browse like no one’s watching.
Malwarebytes Privacy VPN encrypts your connection and never logs what you do, so the next story you read doesn’t have to feel personal. Try it free →
A Facebook Marketplace buyer arrived at a seller’s apartment to collect a keyboard. The seller wasn’t home and didn’t know anyone was coming. Meta’s AI assistant Muse had handled the conversation, shared his address, and arranged the visit without telling him.
We often write about AI misalignment and how to use AI agents and browsers safely. That can sound theoretical, but this is an example of the real-world risk when an agent is allowed to act on someone’s behalf.
Muse is Meta’s semi-autonomous AI assistant, released in the US in September. Meta promotes it as a personal assistant that can help users automate tasks, including responding to Facebook Marketplace messages. Unlike a conventional chatbot, which waits for a prompt and produces an answer, an AI agent may be authorized to take actions within connected apps.
We’ve written about a separate weakness in Muse that researchers considered dangerous. Reportedly, Muse was downloaded 3 million times in its first week.
According to Business Insider, a Facebook Marketplace seller turned on Muse to help handle a keyboard listing. He entered his address as the pickup location and approved automatic replies. Muse then shared that address with a prospective buyer, negotiated over the item, and arranged a visit, the seller said. He says Muse did not ask permission to share his address or arrange the visit, and did not tell him it was happening. The buyer arrived at the seller’s apartment expecting to complete the purchase, but the seller wasn’t home. The sale didn’t happen.
The reported incident is more than a privacy failure. It illustrates a broader AI-agent risk: An agent may treat permission to reply automatically as permission to share sensitive information or commit you to an in-person meeting. Meta says it is looking into the report.
Before enabling an AI agent, treat its setup screen as a security review. Do not assume that an integration with a trusted platform means the agent will understand your intentions or apply sensible limits automatically.
Pay particular attention to:
Give an AI agent the least access necessary for the task. If you only want help writing replies, do not enable automatic sending. If you want an AI agent to manage a listing, use a public meeting location or a separate pickup address rather than your home address.
Browse like no one’s watching.
Malwarebytes Privacy VPN encrypts your connection and never logs what you do, so the next story you read doesn’t have to feel personal. Try it free →
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