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Autonomous AI-powered incident response agent for SIFT Workstation
Autonomous DFIR agent that investigates memory and disk artifacts, corroborates every finding with a second tool, and writes a structured incident report. No human in the loop.
A custom MCP server of 45 read-only, audited tools that let Claude autonomously triage compromised Linux systems and gate its own conclusions through self-correction.
Autonomous DFIR agent — every forensic claim is a signed receipt, deterministically re-derivable from the original image SHA-256.
Marten was built entirely during the submission period. Full codebase — 4-phase agent, 14 Volatility plugins, MCP server, self-correction loop — developed from scratch for FIND EVIL 2026.191
EvidenceLoop helps DFIR analysts triage PCAPs on SIFT while keeping raw evidence local and validating every LLM-assisted finding.
Court-defensible autonomous DFIR. Five orchestrators on one typed MCP server. Real F1 measured across three forensics datasets.
A defensive DFIR agent for Protocol SIFT / Valhuntir. Code-enforced staging, boundary register, per-claim responsibility ledger.
MCP server that enforces forensic evidence integrity through architecture -- no write tools exist, SHA-256 sealing, and a DRS confidence gate.
AI agent that classifies logs, investigates with SIFT tools, and predicts attacks using a persistent behavioral graph and 4-lens self-correction.
A Protocol SIFT extension that teaches the AI to double-check its own work, reducing hallucinations and making automated forensics results more reliable.
We are closing the adversary speed gap. LogPose deploys a specialized AI crew via strict MCP endpoints, autonomously executing SIFT diagnostics to triage and self-correct in seconds
Transforming the SIFT Workstation into an autonomous, self-correcting threat hunting and digital forensics expert using Protocol SIFT.
A Gemini incident-response agent that walks 7 Protocol SIFT MCP tools and visibly self-corrects when surface malware indicators get overturned by deeper forensic evidence.
An autonomous AI defender for Windows DFIR that catches AI-using attackers, audits its own findings with a deterministic critic, and trains itself daily on the latest threat intel.
An autonomous DFIR agent using MCP to wrap Volatility 3 — eliminates context flooding, syntax hallucination, and false clean declarations from AI-driven memory forensics
Sentinel-MCP: Zero human input. Zero hallucinations. Total forensic visibility.
An automated DFIR agent with multi-tool orchestration, artifact deduplication, and self-correction for 100% detection and zero false positives.
Evidence-safe autonomous DFIR agent for Protocol SIFT that self-corrects, proves evidence integrity, and reports traceable findings in seconds.
Read-only DFIR triage agent that hashes evidence, correlates artifacts, scores risk, and visibly self-corrects unsupported claims.
AI incident response agent that livestreams threat-hunting reasoning to an interactive attack graph — and self-corrects when it hits false positives.
A forensic AI agent that catches its own mistakes. Every finding traces back to a specific tool call. No hallucinations reach the report.
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