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Field notes on securing AI agents: threat research on the attacks that work, technical papers on the controls that hold, and guides for the people who run them.

Pieces
57
Threat research
16
Updated
Oct 20, 2026

Latest

Guide11 min read

Approval fatigue: fewer asks mean more oversight, not less

Human approval for agents fails when people get dozens of identical prompts a day. The case for asking less: ask by consequence, turn repeated asks into scoped grants, remember only similar calls, budget approvals, and build screens a person can decide on in ten seconds.

Sam O.Read →

+New here

Start with these

MCP and the tool supply chain

What you install, what a server tells your agent, and whose consent a proxy spends.

All 5

Prompt injection and exfiltration

Instructions that arrive as data, and the channels that carry your data back out.

All 6

Identity, credentials and access

Whose key the agent holds, what a connected account really allows, and where access gets decided.

All 6

Approvals and enforcement

Deciding each action before it runs, asking people only when it matters, and failing safely.

All 7

Coding and computer-use agents

Agents with a shell, a browser or a repository, and the boundaries that keep production out of reach.

All 4

Testing, red teaming and measurement

Threat models, red teams, false positives and the numbers that show a control works without breaking work.

All 7

Running the program

Owners, boards, auditors, budgets and the incident you plan for before it happens.

All 10

Shadow AI and data

The AI already in use, where prompts travel, and policies people will actually follow.

All 5

Essay series · 7 parts

A Century of Possibility

By Sam O.

Seven essays on what a hundred years of invention teach about the arrival of AI: in care, classrooms, factories, markets and institutions, and why capability alone has never been enough.

Start with part one
  1. 01The century that rewired human possibilityFrom 1926 to 2026: how electricity, medicine, computing, networks, and AI expanded human capability, and why invention alone never guaranteed progress.
  2. 02When intelligence becomes infrastructureWhy AI’s economic importance depends on workflow redesign, human expertise, and the difficult journey from a capable model to a useful institution.
  3. 03A second pair of eyes: AI and the work of careHow AI can strengthen medicine and scientific discovery, and why a correct prediction is only one step toward a better human outcome.
  4. 04The classroom after the answer machineAI can make explanations abundant. Education must still teach people to question, practice, judge, and understand without outsourcing the work of learning.
  5. 05AI returns to the physical worldFactories, farms, energy systems, and weather reveal why the future of intelligence still depends on sensors, materials, maintenance, and physical limits.
  6. 06The economy of decisionsHow AI may reshape finance, public services, small business, and work, and why faster decisions still need reasons, accountability, and a fair distribution of value.
  7. 07The future needs more than intelligenceAs AI moves from producing answers to taking action, human progress depends on judgment, permission, accountability, and institutions capable of learning.

+The index

Every piece, newest first

57 pieces

  1. Threat research366 ways to make a destructive action look harmless
  2. Threat researchPolicy active is not an attack: the false positives that stop real agent work
  3. Threat researchWhat deterministic layers catch on their own: a red-team baseline with the AI judge off
  4. Threat researchRules files and self-approval: how coding assistants get reconfigured by the code they read
  5. Threat researchSlopsquatting: the install is the attack, not the hallucination
  6. Threat researchAI incident review: September–October 2026
  7. GuideApproval fatigue: fewer asks mean more oversight, not less
  8. EssayThe century that rewired human possibility
  9. EssayWhen intelligence becomes infrastructure
  10. EssayA second pair of eyes: AI and the work of care
  11. EssayThe classroom after the answer machine
  12. EssayAI returns to the physical world
  13. EssayThe economy of decisions
  14. EssayThe future needs more than intelligence
  15. Threat researchThe confused deputy in MCP OAuth proxies: consent that belongs to someone else
  16. GuideSeen is not protected: six coverage states between discovery and enforcement
  17. GuideOAuth connects the account. Policy governs the action.
  18. GuideWhose key is the agent using? The credential lifecycle from first grant to revocation
  19. GuideCoding agents need broad access. Production should not be part of it.
  20. Threat researchCross-tool data laundering: when every call is allowed and the export is not
  21. GuideYour internal assistant answers anyone with anything in the index. Fix it before retrieval.
  22. GuideWhen the policy check fails: the questions to settle before agent enforcement goes down
  23. GuideMeasure agent security on two columns: the harm that got through and the work that got stopped
  24. Threat researchPersistent memory poisoning: the incident that comes back after you close it
  25. GuideAn incident response playbook for an agent that crossed its authority
  26. GuideThe first 90 days of an agent security program: authority first, policy later
  27. Technical paperThe loosening hidden in a tightening: shipping agent policy changes with replay
  28. Threat researchBefore the first tool call: SSRF in MCP discovery and local launch as code execution
  29. Threat researchPrompt injection beyond text: six myths about images, documents and audio
  30. Threat researchApproved is not executed: replay, substitution and check-to-use gaps in agent approvals
  31. Threat researchRug pulls and tool poisoning: an MCP approval has to cover the bytes, not the name
  32. Technical paperTenant isolation when every customer shares the model
  33. Threat researchInvisible instructions: Unicode tag characters and ASCII smuggling against LLMs
  34. Technical paperThe cost of a guardrail: latency and inference budgets for runtime AI security
  35. GuideWhat an AI security incident costs, and how to model one for an agent
  36. NewsWhen agents delegate to agents: what A2A verifies, and what your chain still has to
  37. GuideShadow AI: your team already uses it, and a ban will not change that
  38. NewsEchoLeak and the exfiltration channel in your assistant's renderer
  39. GuideWhat a board should ask about AI agents, and what good answers sound like
  40. GuideBuying AI security: ten checks that separate real controls from theater
  41. NewsThe MCP supply chain is your package supply chain, with your agent's keys attached
  42. GuideVendor agents in your systems: scope, logs and a kill switch that works
  43. NewsIndirect prompt injection is now an operations problem
  44. GuideWhat auditors ask about AI agents, and the evidence that answers them
  45. Technical paperSecuring agents that click: computer-use and browser agents
  46. NewsAugust 2, 2026: what the EU AI Act now asks of agent deployers, and what NIST has started
  47. Threat researchMalicious model files: the questions to answer before anyone calls torch.load
  48. Technical paperRed teaming AI agents as a continuous program, not an event
  49. GuideData residency for LLM traffic: where prompts go and how to keep them there
  50. Threat researchAI spend is a security signal: anatomy of a runaway agent's night
  51. GuideDue diligence for the AI features already inside your SaaS
  52. GuideWhy AI pilots stall at security review, and the kit that gets them through
  53. GuideAn AI acceptable-use policy people will actually follow
  54. GuideGuardrails developers won't route around: a checklist for the governed path
  55. Technical paperWhat to record for every agent action: a security telemetry schema
  56. GuideThreat model an AI agent in one afternoon
  57. GuideNobody owns the agents: fixing AI accountability before the first incident

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