Marit Halversen
Covers AI governance and regulatory design, with a focus on how compliance obligations land on architecture ra…
Risk desk
Tobias Lindqvist
Adversarial machine learning and the security properties of retrieval systems.
- Risk correspondent
- Risk
- Articles
- 17
- Languages
- EN · NL
Articles by Tobias Lindqvist
RSS for this author →- 08/09/2026 ChatGPT connected to Gmail, Drive, Teams and GitHub: what to check now about your connectors
- 01/09/2026 AI companies warn: serious cyber threat from AI agents within months
- 31/08/2026 Hallucination detection for LLMs in 2026: why teams build a layered stack instead of one tool
- 21/08/2026 Why accuracy is not reliability for business-critical AI
- 21/08/2026 Knowledge bases as an attack surface: why RAG poisoning is an architectural problem
- 20/08/2026 Prompt injection in AI agents is an architecture flaw, not a model bug
- 19/08/2026 Why verification with a single AI model reaches its limits
- 18/08/2026 AI answers are time-bound: why outdated source data is a risk in its own right
- 16/08/2026 Tool Use by AI Systems as Its Own Risk Layer
- 14/08/2026 Multilingual AI verification: why every translation is a separate claim
- 11/08/2026 Why long AI summaries call for claim-by-claim verification
- 10/08/2026 Numbers from AI are claims, not facts: why schema checks are not enough
- 01/08/2026 Data leaks between users and sessions are a design problem
- 31/07/2026 Red teaming of AI agents becomes a continuous process
- 31/07/2026 Indirect prompt injection via documents and websites in 2026
- 30/07/2026 Multi-model verification in 2026: where models correct each other and jointly miss
- 24/07/2026 Prompt injection in AI agents: architecture and compliance problem
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