Forensia CTI Core

Summary

Ingested excerpt (first ~500 chars of normalized text).

Build real agentic apps using CUGA: two dozen working examples on a lightweight harness Build real agentic apps using CUGA: two dozen working examples on a lightweight harness Hugging Face Models Datasets Spaces Buckets new Docs Enterprise Pricing Website Tasks HuggingChat Collections Languages Organizations Community Blog Posts Daily Papers Learn Discord Forum GitHub Solutions Team & Enterprise Hugging Face PRO Enterprise Support Inference Providers Inference Endpoints …

https://huggingface.co/blog/ibm-research/cuga-apps

sha256:cd9045c69cd17a5504035d3dcf68bc9016a6337b73eba05bcd73702c1fd2c73b

What we pulled out

Deterministic extractor (IOC + allowlisted tokens + ATT&CK IDs present in DB).

cve0
md50
url2
ipv40
ipv60
sha10
domain10
sha2560
malware_token0
attack_pattern0
threat_actor_token0

Indicators

Linked with report → mentions → indicator. Values open the indicator workspace.

Type	Value	Link
domain	github.com	Open →
domain	os.getenv	Open →
domain	skill.md	Open →
domain	copied.you	Open →
domain	agent.invoke	Open →
domain	main.py	Open →
domain

Malware families

Allowlist token matches only.

None extracted.

Threat actors mentioned

Allowlist mentions — not a formal attribution verdict.

None extracted.

ATT&CK techniques

MITRE IDs referenced in text and present in local technique table.

None linked (import ATT&CK or adjust text).

CONTINUE INVESTIGATION

High-signal pivots without leaving the thread you started in search.

All reports
Browse the report corpus.
Intel graph (first IOC)
Neighborhood from the first linked indicator.

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