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Can AI Keep Up with Its Own Security Risks?

As AI-generated code proliferates, vulnerabilities abound, and experts sound the alarm

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The rapid advancement of artificial intelligence (AI) has brought about unprecedented opportunities for innovation, but it also poses significant security risks. As AI-generated code becomes increasingly prevalent, the...

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Multi-SourceSource gap: More sources needed

What Happened

Microsoft's AI red team, launched in 2019, was initially met with skepticism. However, the arrival of GPT-4 forced the team to reevaluate its...

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1 / 7

Microsoft's AI red team, launched in 2019, was initially met with skepticism. However, the arrival of GPT-4 forced the team to reevaluate its approach. "The tool that we had changed; actually, it broke," says Ram Shankar Siva Kumar, who leads the team. The team had to retool and rethink its methodologies to address the unique challenges of securing AI systems.

Meanwhile, Ivanti has released patches to address critical vulnerabilities in its Sentry secure mobile gateway solution, including a maximum-severity flaw that enables remote attackers to execute code with root privileges. The company has no evidence that the vulnerabilities are being exploited in the wild.

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Why It Matters

The security risks associated with AI-generated code are well-documented. A report from Checkmarx reveals that enterprises are shipping AI-generated...

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The security risks associated with AI-generated code are well-documented. A report from Checkmarx reveals that enterprises are shipping AI-generated code despite knowing it is vulnerable. The survey of 2,350 security leaders exposes an underlying naivete about AI-built code and its vulnerabilities.

"The advantage will belong to the side that can get the most out of these tools," warns Anthropic, the developer of the powerful AI model Mythos. "In the short term, this could be attackers, if frontier labs aren't careful about how they release these models. In the long term, we expect it will be defenders who will more efficiently direct resources and use these models to fix bugs before new code ever ships."

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Key Numbers

42%: The percentage of security leaders who believe AI-generated code is more secure than human-written code (Checkmarx report)

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  • **42%: The percentage of security leaders who believe AI-generated code is more secure than human-written code (Checkmarx report)

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What Experts Say

Mythos-class models collapse the window between a vulnerability existing and a working exploit being available from months to minutes." — Checkmarx...

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"Mythos-class models collapse the window between a vulnerability existing and a working exploit being available from months to minutes." — Checkmarx report
"We had to retool completely, and we also had to rethink what it means to red team an AI system." — Ram Shankar Siva Kumar, Microsoft AI red team lead

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Background

The UK's proposed content filtering has raised concerns among CISOs, who worry that the same technology could undermine enterprise security. The...

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The UK's proposed content filtering has raised concerns among CISOs, who worry that the same technology could undermine enterprise security. The proposal requires tech companies to create device controls to block children from viewing or creating sexually explicit imagery.

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What Comes Next

As AI continues to evolve, the security risks associated with AI-generated code will only continue to grow. It is essential for enterprises to...

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As AI continues to evolve, the security risks associated with AI-generated code will only continue to grow. It is essential for enterprises to prioritize security and take a proactive approach to addressing these risks. The development of more advanced AI red teaming methodologies and the implementation of robust security measures will be crucial in mitigating these risks.

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5 cited references across 2 linked domains.

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5 cited references across 2 linked domains. Source gap watch: More sources needed.

  1. Source 1 · Fulqrum Sources

    Ivanti: Max severity Sentry flaw allows code execution as root

  2. Source 2 · Fulqrum Sources

    Enterprises know AI-generated code is vulnerable; they’re shipping it anyway

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🔒 Security Alert

Can AI Keep Up with Its Own Security Risks?

As AI-generated code proliferates, vulnerabilities abound, and experts sound the alarm

Friday, June 19, 2026 • 3 min read • 5 source references

  • 3 min read
  • 5 source references

The rapid advancement of artificial intelligence (AI) has brought about unprecedented opportunities for innovation, but it also poses significant security risks. As AI-generated code becomes increasingly prevalent, the question of whether AI can keep up with its own security risks has become a pressing concern.

Story pulse
Story state
Deep multi-angle story
Evidence
What Happened
Coverage
7 reporting sections
Next focus
What Comes Next

What Happened

Microsoft's AI red team, launched in 2019, was initially met with skepticism. However, the arrival of GPT-4 forced the team to reevaluate its approach. "The tool that we had changed; actually, it broke," says Ram Shankar Siva Kumar, who leads the team. The team had to retool and rethink its methodologies to address the unique challenges of securing AI systems.

Meanwhile, Ivanti has released patches to address critical vulnerabilities in its Sentry secure mobile gateway solution, including a maximum-severity flaw that enables remote attackers to execute code with root privileges. The company has no evidence that the vulnerabilities are being exploited in the wild.

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Why It Matters

The security risks associated with AI-generated code are well-documented. A report from Checkmarx reveals that enterprises are shipping AI-generated code despite knowing it is vulnerable. The survey of 2,350 security leaders exposes an underlying naivete about AI-built code and its vulnerabilities.

"The advantage will belong to the side that can get the most out of these tools," warns Anthropic, the developer of the powerful AI model Mythos. "In the short term, this could be attackers, if frontier labs aren't careful about how they release these models. In the long term, we expect it will be defenders who will more efficiently direct resources and use these models to fix bugs before new code ever ships."

Key Numbers

  • **42%: The percentage of security leaders who believe AI-generated code is more secure than human-written code (Checkmarx report)

What Experts Say

"Mythos-class models collapse the window between a vulnerability existing and a working exploit being available from months to minutes." — Checkmarx report
"We had to retool completely, and we also had to rethink what it means to red team an AI system." — Ram Shankar Siva Kumar, Microsoft AI red team lead

Key Facts

Background

The UK's proposed content filtering has raised concerns among CISOs, who worry that the same technology could undermine enterprise security. The proposal requires tech companies to create device controls to block children from viewing or creating sexually explicit imagery.

What Comes Next

As AI continues to evolve, the security risks associated with AI-generated code will only continue to grow. It is essential for enterprises to prioritize security and take a proactive approach to addressing these risks. The development of more advanced AI red teaming methodologies and the implementation of robust security measures will be crucial in mitigating these risks.

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Unmapped Perspective (5)

bleepingcomputer.com

Ivanti: Max severity Sentry flaw allows code execution as root

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bleepingcomputer.com

Unmapped bias Credibility unknown Dossier
bleepingcomputer.com

Anthropic rolls out Claude Fable 5, but it's available for a limited time

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bleepingcomputer.com

Unmapped bias Credibility unknown Dossier
csoonline.com

AI red teaming comes of age

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csoonline.com

Unmapped bias Credibility unknown Dossier
csoonline.com

UK move to filter photos and messages triggers encryption worries for CISOs

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csoonline.com

Unmapped bias Credibility unknown Dossier
csoonline.com

Enterprises know AI-generated code is vulnerable; they’re shipping it anyway

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csoonline.com

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Emergent News uses automated assistance to gather, compare, and summarize coverage from 5 cited sources. Review the source list below before relying on the story.