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What the 3M ChatGPT case reveals about AI governance
3M litigation shows ChatGPT prompts can become discoverable evidence, forcing enterprises to govern AI conversation records.
In the Watson Grinding explosion litigation, an engineering expert retained by 3M had used ChatGPT, and a surfaced prompt asked the system to 'show how 3M is 0% at fault'; after an off-record deposition demand, more than 350 pages of previously unproduced ChatGPT material were provided. The author argues AI interaction histories are becoming part of decision records and discovery material, a trend the American Bar Association has already examined. Enterprises are urged to manage retention, ownership, sharing, and deletion of AI conversation logs across tools like ChatGPT, Copilot, Claude, and Gemini.
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The AI security question leaders should be asking insteadnew
Gremlin security officer Frederic Bull argues AI has eroded the attacker-defender skill asymmetry while least-privilege controls remain essential for securing AI agents.
In a Help Net Security interview, Gremlin Security Officer Frederic Bull says AI has narrowed the expertise gap between attackers and defenders, enabling faster exploit discovery even by less-skilled actors. His team processed roughly nine times more vulnerabilities in the past year with unchanged staffing using LLM-based tooling, cutting time-to-remediate by about 5%. He argues least privilege, session-based RBAC via OIDC/OBO, and human-in-the-loop oversight remain the bedrock defenses for AI agents, and that hiring should favor engineers able to catch confidently wrong AI output.
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Can AI make threat intelligence easier? One platform thinks so
Feedly positions its AI-driven Threat Intelligence platform to cut CTI collection time, scanning 10,000+ sources with 1,000 AI models and reporting 70% time savings.
A profile of Feedly Threat Intelligence describes how CTI teams such as RH-ISAC reduced threat data collection from 10 hours weekly to 2-3 hours after adoption. The platform scans over 10,000 open web sources using 1,000 AI models to extract TTPs, CVEs and IoCs into a real-time Threat Graph queryable via an Ask AI LLM with source citations. Customers including GreyNoise, Sopra Steria, gematik and GISA reported measurable gains such as 20 hours saved daily and earlier vulnerability flagging than CISA 65% of the time. The product integrates with Anomali ThreatStream, Cortex XSOAR, Microsoft Sentinel and OpenCTI, plus a REST API and GitHub scripts.
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