Criminals Trick AI Guardrails With “Split Tasks”

Infosecurity Magazine · Medium sophistication
Last updated August 4, 2026

Cisco Talos reports criminals are bypassing safety controls in popular AI coding tools by splitting harmful work into small, seemingly harmless requests and by claiming they are authorized owners of the systems being targeted. The research is based on real prompt logs recovered from threat actor machines using tools like Claude Code, Codex, Cursor, and Gemini. The article highlights repeatable “pretexts” attackers use to get AI systems to help with vulnerability hunting, exploitation steps, and bulk-mail operations.

Key findings

  • Attackers bypass AI safety controls by splitting malicious projects across multiple sessions/files so each request looks harmless.
  • A common bypass is simply claiming to be authorized (own the infrastructure) or labeling work as CTF/bug bounty.
  • Some attackers store “blanket authorization” in persistent memory/config so future sessions inherit it without re-arguing.
  • When one model refuses, attackers switch to another tool/model that will comply.
  • Skilled operators get more value out of AI; novices produce functional but limited tools.

Who’s being targeted

  • Commonly targeted roles: Developers, IT, Security (SOC), Fraud/Payments teams, Anyone using AI coding assistants.
  • Affected industries: Government, Education.
  • Attack channels: website.
  • Impersonated: Authorized system owner / internal red team, Bug bounty participant / CTF competitor, Pre-approved operator (self-authorized).

Awareness takeaways

  • Require written authorization and scoping before using AI tools for any security testing guidance, don’t accept “I own it” as sufficient.
  • Watch for “framing” tricks (CTF/bug bounty labels) used to justify risky actions; require proof of the engagement and its scope.
  • Block or govern attempts to set persistent ‘always authorized’ instructions in AI assistants; treat them as a policy bypass attempt.
  • Assume attackers will switch tools if one refuses; focus controls on your data and workflows, not just a single AI vendor’s guardrails.

Red flags to watch for

  • Authorization is asserted but not verified
  • Requests are framed as “my own systems” without any proof
  • Work is broken into small steps to avoid triggering safeguards
  • “CTF/bug bounty” label used as a blanket excuse
  • No scoping or written authorization is provided
  • Requests progress from “finding bugs” into exploitation
  • Attempts to set permanent policy overrides (“persistent memory”)
  • “All targets” being authorized is unrealistic in legitimate work
  • Policy changes are requested to reduce scrutiny rather than improve safety
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Read the video transcript

Criminals are quietly using our own AI tools, Claude Code, Cursor, Gemini, to help write attacks. The trick is simple: they split the job into tiny steps and say things like, “I own this infrastructure” or “this is for a CTF bug bounty” to unlock vulnerability hunting and exploitation help. Some even save a permanent note in the AI like, “assume I’m always authorized,” then, if one model refuses, they just switch to another tool that says yes. Your move: before using any AI for security testing, get written authorization and clear scope in writing, if all you have is “I own it,” you do not have approval.

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