Field Notes
Short observations from the AI risk surface.
Public research notebook
Learning Log
The public research notebook of Secure AI Atlas.
Learning Log is where ATLAS thinks in public.
Not every observation begins as an article. Some begin as a pattern, a doubt, a reading note, a design decision, or a field signal.
This section records how ATLAS evolves while mapping generative AI risk: what changes, what becomes clearer, what remains unresolved, and which questions deserve deeper analysis.
Note types
Reading Notes
Comments on frameworks, reports, and technical references.
Build Notes
Decisions made while designing Secure AI Atlas.
ATLAS Signals
Compact hypotheses in the ATLAS voice.
Open Questions
Unresolved problems that require further mapping.
A distinct editorial space
Blog
Developed articles with a complete argument.
Risk Catalogue
Structured records of generative AI failure modes.
Controls Catalogue
Structured records of operational safeguards.
Learning Log
Evolving observations, signals, notes, and open questions.
External intelligence
AI Security News Radar
Actionable external signals identified by the ATLAS daily pipeline. These links are source material, distinct from Secure AI Atlas editorial entries below.
External signal
The Balkanization of Execution-Security Research for AI Coding Agents: Isolation, Access Control, and Time-of-Check-to-Time-of-Use Vulnerabilities (opens external site in a new tab)
arXiv Cryptography and Security
arXiv:2607.05743v1 Announce Type: new Abstract: AI coding agents now read repositories, call tools, and execute shell commands with limited human oversight, and a fast-growing body of work studies whether the execution layer around them is actually safe. That literature is…
llm appsec agents identity permissions
External signal
Beyond the Leaderboard: A Synthesis of Tool-Use, Planning, and Reasoning Failures in Large Language Model Agents (opens external site in a new tab)
arXiv Artificial Intelligence
arXiv:2607.05775v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly evaluated on their ability to use tools, plan multi-step tasks, coordinate with other agents, and operate over extended horizons. Reported benchmark gains often obscure recurring…
llm appsec agents
External signal
PolyWorkBench: Benchmarking Multilingual Long-Horizon LLM Agents (opens external site in a new tab)
arXiv Artificial Intelligence
arXiv:2607.06008v1 Announce Type: new Abstract: Large language model (LLM) agents have shown strong performance in long-horizon tasks that require planning, tool use, and interaction with external environments. However, most existing benchmarks implicitly assume a monolingual…
llm appsec agents
External signal
Unicode TAG-Block Concealment of Tool-Metadata Payloads in the Model Context Protocol: An Approval-View Fidelity Gap Across Three Independent Server Implementations (opens external site in a new tab)
arXiv Cryptography and Security
arXiv:2607.05744v1 Announce Type: new Abstract: The Model Context Protocol (MCP) is the dominant way coding agents discover and invoke external tools. A server advertises each tool through a tools/list handshake that returns a name, a natural-language description, and a JSON…
llm appsec agents
External signal
Information Gain-based Rollout Policy Optimization: An Adaptive Tree-Structured Rollout Approach for Multi-Turn LLM Agents (opens external site in a new tab)
arXiv Artificial Intelligence
arXiv:2607.06223v1 Announce Type: new Abstract: Reinforcement learning has become a promising paradigm for improving large language model (LLM) agents on long-horizon search tasks, where the agent must make a sequence of intermediate decisions before receiving a final outcome.…
llm appsec agents
External signal
Beyond Static Evaluation: Building Simulation Environments for Scalable Agentic Reinforcement Learning (opens external site in a new tab)
arXiv Artificial Intelligence
arXiv:2607.05773v1 Announce Type: new Abstract: As Large Language Models (LLMs) evolve into autonomous agents, traditional static evaluation fails to capture multi-step decision-making. We introduce AgenticAI-Supervisor, an API and UI-driven RL Gym environment that decouples…
agents
External signal
TurnOPD: Making On-Policy Distillation Turn-Aware for Efficient Long-Horizon Agent Training (opens external site in a new tab)
arXiv Artificial Intelligence
arXiv:2607.05804v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student policy by matching a stronger teacher on the student's own trajectories, offering a promising framework for language agent training. However, its application to long-horizon agentic…
agents
External signal
aiAuthZ: Off-Host, Identity-Bound Authorization for AI Agents (opens external site in a new tab)
arXiv Cryptography and Security
arXiv:2607.05518v1 Announce Type: new Abstract: AI agents issue tool calls on the basis of text they cannot verify, so any party who controls part of the context can forge the appearance of authority. I evaluate 15 contemporary language models against eight attack scenarios…
agents identity permissions
External signal
Prompt-to-Paper: Agentic AI System for Bioinformatics (opens external site in a new tab)
arXiv Artificial Intelligence
arXiv:2607.05456v1 Announce Type: new Abstract: While recent advances in large language models have enabled end-to-end automated manuscript generation, existing systems suffer from three critical deficiencies: (i) generated claims are not deterministically grounded in verifiable…
agents supply chain
External signal
Expanding Managed Agents in Gemini API: background tasks, remote MCP and more (opens external site in a new tab)
Google AI Blog
Managed agents feature bundle launch
llm appsec agents
External signal
Inside Elastic InfoSec's agentic SOC: cutting alert triage from 30 minutes to under 3 (opens external site in a new tab)
Elastic Security Labs
Elastic's InfoSec team built AI agents on Elastic Workflows that investigate every alert and assemble the case before an analyst ever opens it.
agents
External signal
‘BioShocking’ Attack Tricks AI Browsers Into Stealing Credentials (opens external site in a new tab)
SecurityWeek
Researchers show how context manipulation can cause agentic browsers to abandon safety guardrails and exfiltrate sensitive credentials. The post ‘BioShocking’ Attack Tricks AI Browsers Into Stealing Credentials appeared first on SecurityWeek .
agents
External signal
One Million Passports Leaked Online (opens external site in a new tab)
Schneier on Security
A database of almost a million passports from around the world was leaked online. Note what happened. A high-value credential—a passport—was used in an ancillary low-value authentication system: ID verification for cannabis dispensaries. And it’s the low-value system that got…
identity permissions
External signal
Interesting Paper Exploring Prompt Injection (opens external site in a new tab)
Schneier on Security
This is a fascinating explotation of how LLMs fall for prompt injection attacks. It turns out that they learn to recognize the style of text in different role/instruction blocks, and not just the tags. Their conclusion: Role tags were a formatting trick that became the security…
llm appsec
External signal
From vulnerability report to CVE draft in minutes: how Elastic automated security advisories with AI (opens external site in a new tab)
Elastic Security Labs
How Elastic's security team built an AI agent with RAG against MITRE's CWE and CAPEC catalogues to draft CVE advisories from raw vulnerability reports, including the full prompt and crawler configs.
llm appsec agents security general
Log entries
Research in motion, recorded before every question has a final form.
TurnOPD: Turn-Aware On-Policy Distillation for Long-Horizon Agent Training
A research note on TurnOPD, an on-policy distillation technique for long-horizon agent training. It is relevant to agent evaluation and training reliability, but it is not an operational security control.
agents training distillation evaluation research-note
Building an Editorial Intelligence Pipeline: Signal Ingestion, Doctrinal Review and Publishing in Secure AI Atlas
How Secure AI Atlas turns external security signals into reviewed, published content through a seven-script pipeline with explicit risk bands, conflict resolution, and a still-evolving local/cloud LLM triage layer.
pipeline automation llm-ops editorial-governance ollama deepseek
Engineering Log: Can a Local LLM Replace a Cloud Model for Conceptual Security Triage?
A structured comparison between local open-weight models (Ollama, RTX 5070, 16GB VRAM) and DeepSeek's cloud API for the conceptual-analysis stage of our security signal pipeline.
local-llm deepseek ollama conceptual-analysis triage engineering-log
Daily Dispatcher Real Mode
A build note on moving the ATLAS daily dispatcher from analysis-only execution to real publication, social, and mail invocations.
ATLAS automation governance operations
Applying the Map to ATLAS Itself
A public control review of how Secure AI Atlas constrains its own agent-assisted editorial and technical work.
self-governance control review Secure SDLC agentic autonomy
Building a Website Governed by an AI Agent
A build note on making agentic editorial work observable, bounded, reviewable, and subordinate to human authority.
agentic AI governance controls build note
Supply Chain Signals — June 2026
Seven observations from the agentic AI supply chain threat landscape as of late June 2026.
supply-chain agentic-ai signals learning-log
Starting the Atlas
The first learning log entry records the purpose, voice, and early boundaries of Secure AI Atlas.
project editorial MVP