zettelforge
Active·★ 40·MIT·Updated 2026-05-28
★ Trending★ Memory & Context★ Security & Safety
ZettelForge - Agentic Memory System for Cyber Threat Intelligence
ZettelForge provides persistent memory for AI agents with automatic entity extraction, knowledge graph construction, and STIX ontology. It supports offline operation with no API keys or cloud dependencies. It features alias resolution, blended retrieval, and memory evolution for cyber threat intelligence.
#ai-agent#claude-code#claude-code-plugin#cti#cybersecurity#hermes-agent#knowledge-graph#llm
01
Features
01Entity extraction of CVEs, threat actors, IOCs, MITRE ATT&CK techniques, and more
02Knowledge graph with causal triple inference
03Alias resolution (e.g., APT28 = Fancy Bear)
04Blended retrieval combining vector similarity and graph traversal with intent classification
05Memory evolution with ADD/UPDATE/DELETE/NOOP decisions
02
Compatibility
Python
Python 3.10+
Verified via docs
03
Quick start
1
$ pip install zettelforge
04
Use cases
↳Persistent memory for AI agents in cyber threat intelligence
↳Threat intelligence analysis and knowledge graph building
↳Tracking changes in threat actor tactics and techniques over time
05
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Comments
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- Sasha RiveraMay 26, 2026
Threat intelligence memory that persists across agent runs is genuinely useful.
- FFinley KimMay 25, 2026
The Zettelkasten-style linking makes related IOCs and TTPs discoverable.
- TTaylor WilsonApr 23, 2026
MCP integration lets you query the knowledge base from agent workflows.
- EElliot ThompsonApr 8, 2026
Good fit for CTI workflows where context accumulates over time.