Attacks & Vulnerabilities
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The security principles guiding 1Password's approach to AI (5 minute read)
Seven core security principles for AI integration: encrypting secrets, using deterministic authorization over probabilistic LLM decisions, preventing raw credentials in LLM contexts, maintaining auditability, ensuring transparency, implementing least privilege, and balancing security with usability. AI agents must follow strict access controls, similar to humans, with credentials delivered securely (e.g., OAuth) rather than through LLM prompts, maintaining a zero-knowledge architecture. These principles show that traditional siloed privileged access management is inadequate for the AI era, which will require unified frameworks for both human and AI interactions.
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Three Dots to Root: How I Found a Path Traversal in Microsoft's Agentic Web (6 minute read)
Microsoft's NLWeb is a new framework designed to allow AI agents to interact with websites and APIs via natural language. This author describes how they discovered a path traversal vulnerability that could lead to the disclosure of arbitrary files such as `/etc/passwd` or `.env`. The vulnerability was caused by the use of the `os.path.normpath()` function, which does not prevent “climbing out” of the directory using `../`.
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Constructing a Trustworthy Evaluation Methodology for Contextual Security Analysis (7 minute read)
DryRun Security uses an AI engine called Contextual Security Analysis (CSA) to analyze code changes probabilistically. Each PR goes through three steps: whole-PR synthesis to understand the goal, hunk-scoped reasoning to isolate individual code hunks and filter out unrelated changes, and on-demand context acquisition to retrieve supporting files and dependencies. DryRun also has a secondary audit model that randomly samples production findings every 24 hours to check instruction compliance, hallucination detection, and vulnerability accuracy.
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EPSS Pulse (Product Launch)
RunZero's EPSS Pulse is a free tool that tracks trends in Exploit Prediction Scoring System (EPSS) data to help security teams prioritize vulnerability remediation. It shows which vulnerabilities are gaining or losing exploitation likelihood over time, helping defenders focus on critical patches. Monitoring EPSS score changes enables organizations to make better vulnerability management decisions beyond static CVSS scores.
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Tonic Security (Product Launch)
Tonic Security provides an AI agent–driven exposure management platform that ingests org data and threat intel to contextualize risk, prioritize remediation, reduce alert noise, and accelerate fixes. The company claims 50% faster MTTR and 90% fewer remediation actions needed.
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Utilities, Factories at Risk From Encryption Holes in Industrial Protocol (3 minute read)
OPC UA, a widely used industrial protocol, contains cryptographic design flaws that enable authentication bypass and message confusion attacks. Researcher Tom Tervoort has disclosed CVEs and PoCs that affect multiple vendors. He recommends applying patches, disabling OPC UA over HTTPS and Basic128Rsa15, and enforcing network restrictions like IP allowlists to limit exposure.
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AppSec/ProdSec's Reality Gap (12 minute read)
Application and Product Security face a disparity in connecting theoretical security concepts to practical environments. A lack of context defines the problem space, teams trying to avoid slowing down development, security tools not addressing where teams are struggling or organizational scale, and tooling being designed for gates instead of guardrails. AI-based tools may help in providing more context and tailored experiences, but they will not alleviate the resource constraints that many teams face.
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Thanks for reading,
Prasanna Gautam, Eric Fernandez & Sammy Tbeile
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