Threat Intelligence OSINT
zhaoxuya520/reverse-skill
Enriches IOCs, campaigns, impersonation and scams from public sources, including bounded X search through Xquik, and checks each lead against independent evidence.
Agent skill
Collecting Indicators Of Compromise
Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing.
Install Collecting Indicators Of Compromise
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill collecting-indicators-of-compromise -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills collecting-indicators-of-compromise --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/collecting-indicators-of-compromise .claude/skills/collecting-indicators-of-compromise && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "collecting-indicators-of-compromise" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/collecting-indicators-of-compromise into .claude/skills/collecting-indicators-of-compromise/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "collecting-indicators-of-compromise", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/collecting-indicators-of-compromiseType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill collecting-indicators-of-compromise -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills collecting-indicators-of-compromise --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/collecting-indicators-of-compromise .agents/skills/collecting-indicators-of-compromise && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "collecting-indicators-of-compromise" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/collecting-indicators-of-compromise into .agents/skills/collecting-indicators-of-compromise/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "collecting-indicators-of-compromise", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill collecting-indicators-of-compromise -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills collecting-indicators-of-compromise --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/collecting-indicators-of-compromise .cursor/skills/collecting-indicators-of-compromise && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "collecting-indicators-of-compromise" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/collecting-indicators-of-compromise into .cursor/skills/collecting-indicators-of-compromise/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "collecting-indicators-of-compromise", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git --path skills/collecting-indicators-of-compromise--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill collecting-indicators-of-compromise -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills collecting-indicators-of-compromise --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/collecting-indicators-of-compromise .gemini/skills/collecting-indicators-of-compromise && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "collecting-indicators-of-compromise" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/collecting-indicators-of-compromise into .gemini/skills/collecting-indicators-of-compromise/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "collecting-indicators-of-compromise", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills collecting-indicators-of-compromiseInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill collecting-indicators-of-compromise -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/collecting-indicators-of-compromise .github/skills/collecting-indicators-of-compromise && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "collecting-indicators-of-compromise" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/collecting-indicators-of-compromise into .github/skills/collecting-indicators-of-compromise/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "collecting-indicators-of-compromise", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill collecting-indicators-of-compromise -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills collecting-indicators-of-compromise --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/collecting-indicators-of-compromise .opencode/skills/collecting-indicators-of-compromise && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "collecting-indicators-of-compromise" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/collecting-indicators-of-compromise into .opencode/skills/collecting-indicators-of-compromise/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "collecting-indicators-of-compromise", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
collecting-indicators-of-compromise- GitHub stars
- 34k
- Token cost
- ~2.7k tokens
- SKILL.md length
- 768 words
- Files
- 4 (incl. scripts, references)
- Skills in repo
- 644
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing.
- Works in 6 steps: Identify IOC Categories → Extract IOCs from Evidence Sources → Enrich IOCs with Context → …
- Tasks that involve OSINT
- SKILL.md covers When to Use, Prerequisites, Workflow and Key Concepts, plus 3 more sections
- Runs Python scripts from its folder
What it does
Collecting Indicators Of Compromise is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Covers network, host, email, and behavioral indicators using STIX/TAXII formats and threat intelligence platforms. Activates for requests involving IOC collection, indicator extraction, threat indicator sharing, compromise indicators, STIX export, or IOC enrichment.
Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).
It sits in Security, covering OSINT and Security operations. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.
When your agent uses it
- Tasks that involve OSINT
- Tasks that involve Security operations
Example prompts
- “/collecting-indicators-of-compromise”
Requirements
- Python 3
Workflow steps
6 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Collecting Indicators Of Compromise loads about 2.7k tokens when it runs, and up to ~3.2k if it reads all its reference files. Until then it costs about 122 tokens; SKILL.md has 768 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 768 words, ~2,676 tokens.
Download SKILL.mdSave it as
.claude/skills/collecting-indicators-of-compromise/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- collecting-indicators-of-compromise
- description
- Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Covers network, host, email, and behavioral indicators using STIX/TAXII formats and threat intelligence platforms. Activates for requests involving IOC collection, indicator extraction, threat indicator sharing, compromise indicators, STIX export, or IOC enrichment.
- domain
- cybersecurity
- subdomain
- incident-response
- tags
- IOC-collection, threat-indicators, STIX-TAXII, MISP, threat-intelligence-sharing
- mitre_attack
- T1071.001, T1071.004, T1053.005, T1547.001, T1059.001, T1041
- version
- 1.0.0
- author
- mahipal
- license
- Apache-2.0
- nist_csf
- RS.MA-01, RS.MA-02, RS.AN-03, RC.RP-01
Collecting Indicators of Compromise
When to Use
- During active incident response to identify and block adversary infrastructure
- Post-incident to document all observed adversary artifacts for future detection
- When sharing threat intelligence with ISACs, sector partners, or law enforcement
- When building detection rules in SIEM, EDR, or network security tools
- When enriching IOCs with threat intelligence context for risk scoring
Do not use for behavioral TTP analysis without accompanying technical indicators; use MITRE ATT&CK mapping for behavioral characterization.
Prerequisites
- Access to incident evidence sources: SIEM logs, EDR telemetry, memory dumps, disk images, network captures
- Threat intelligence platform (MISP, OpenCTI, ThreatConnect) for IOC management and sharing
- IOC enrichment tools: VirusTotal, OTX (AlienVault Open Threat Exchange), Shodan, DomainTools
- STIX 2.1 knowledge for structured IOC representation
- Sharing agreements with relevant ISACs (FS-ISAC, H-ISAC, IT-ISAC) or sector partners
Workflow
Step 1: Identify IOC Categories
Collect indicators across all categories from incident evidence:
Network Indicators:
- IP addresses (C2 servers, staging servers, exfiltration destinations)
- Domain names (C2 domains, phishing domains, DGA domains)
- URLs (malware download, C2 check-in, exfiltration endpoints)
- JA3/JA3S hashes (TLS client/server fingerprints)
- User-Agent strings (custom or unusual HTTP headers)
- DNS query patterns (tunneling signatures, DGA patterns)
Host Indicators:
- File hashes (MD5, SHA-1, SHA-256 of malware, tools, scripts)
- File paths (known malware installation directories)
- Registry keys (persistence mechanisms, configuration storage)
- Scheduled tasks and service names (persistence)
- Mutex/event names (malware instance synchronization)
- Named pipes (C2 communication channels, e.g., Cobalt Strike)
Email Indicators:
- Sender addresses and domains (spoofed or attacker-controlled)
- Subject lines and body content patterns
- Attachment names and hashes
- Embedded URLs
- Email header anomalies (SPF/DKIM/DMARC failures)
Step 2: Extract IOCs from Evidence Sources
Systematically extract indicators from each evidence source:
From SIEM/Log Analysis:
# Extract unique destination IPs from firewall logs
index=firewall action=blocked
| stats count by dest_ip
| where count > 100
# Extract domains from DNS query logs
index=dns query=*evil* OR query=*c2*
| stats count by queryFrom Memory Forensics:
# Extract network connections
vol -f memory.raw windows.netscan | grep ESTABLISHED
# Extract strings from suspicious process memory
vol -f memory.raw windows.memmap --pid 3847 --dump
strings -n 8 pid.3847.dmp | grep -E "(http|https)://"From Malware Analysis:
Sandbox Report IOC Extraction:
- Dropped files: 3 (hashes extracted)
- DNS queries: update.evil[.]com, cdn.malware[.]net
- HTTP connections: POST to https://185.220.101[.]42/gate.php
- Registry modified: HKCU\Software\Microsoft\Windows\CurrentVersion\Run\svcupdate
- Mutex created: Global\MTX_0x1234ABCD
- Named pipe: \\.\pipe\MSSE-1234-serverStep 3: Enrich IOCs with Context
Add threat intelligence context to each indicator:
IOC Enrichment Report:
━━━━━━━━━━━━━━━━━━━━━
IP: 185.220.101.42
VirusTotal: 12/89 vendors flag as malicious
Shodan: Open ports: 443, 8443, 80
Geolocation: Netherlands, AS208476
First Seen: 2025-10-01
Threat Intel: Associated with Qakbot C2 infrastructure
Confidence: High
TLP: AMBER
Domain: update.evil[.]com
Registration: 2025-10-28 (recently registered)
Registrar: Namecheap
WHOIS Privacy: Yes
VirusTotal: 8/89 vendors flag as malicious
DNS History: Resolved to 185.220.101.42, 91.215.85.17
Confidence: High
TLP: AMBERStep 4: Score and Prioritize IOCs
Assign confidence and risk scores to each indicator:
| Score | Confidence Level | Criteria |
|---|---|---|
| 90-100 | Confirmed Malicious | Multiple TI sources confirm, observed in active attack |
| 70-89 | Highly Suspicious | Single TI source confirms, behavioral analysis supports |
| 50-69 | Suspicious | Limited TI data, contextually suspicious |
| 30-49 | Unconfirmed | No TI matches, but anomalous in environment |
| 0-29 | Likely Benign | False positive indicators or legitimate infrastructure |
Step 5: Distribute IOCs for Detection and Blocking
Push IOCs to defensive systems for immediate protection:
- Firewall/IPS: Block C2 IPs and domains
- DNS: Sinkhole malicious domains
- EDR: Add file hashes to blocklist, create custom IOC watchlists
- Email Gateway: Block sender domains, attachment hashes, malicious URLs
- SIEM: Create correlation searches for IOC matches
- Web Proxy: Block URLs and domains in web filtering policy
Step 6: Share IOCs with Partners
Package IOCs in STIX 2.1 format for sharing:
{
"type": "indicator",
"spec_version": "2.1",
"id": "indicator--a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"created": "2025-11-15T18:00:00Z",
"modified": "2025-11-15T18:00:00Z",
"name": "Qakbot C2 Server IP",
"indicator_types": ["malicious-activity"],
"pattern": "[ipv4-addr:value = '185.220.101.42']",
"pattern_type": "stix",
"valid_from": "2025-11-15T14:23:00Z",
"confidence": 95,
"labels": ["c2", "qakbot"],
"object_marking_refs": ["marking-definition--f88d31f6-486f-44da-b317-01333bde0b82"]
}Submit to MISP, ISAC portals, and TAXII servers per sharing agreements.
Show full SKILL.md (322 more words)Show less
Key Concepts
| Term | Definition |
|---|---|
| IOC (Indicator of Compromise) | Technical artifact observed during a security incident that indicates adversary presence (hash, IP, domain, etc.) |
| TLP (Traffic Light Protocol) | Standard for classifying the sharing restrictions of threat intelligence: WHITE, GREEN, AMBER, AMBER+STRICT, RED |
| STIX (Structured Threat Information Expression) | Standard language for representing cyber threat intelligence in a structured, machine-readable format |
| TAXII (Trusted Automated Exchange of Intelligence Information) | Transport protocol for sharing STIX-formatted threat intelligence between organizations |
| Confidence Score | Numerical rating (0-100) indicating the analyst's certainty that an indicator is truly malicious |
| IOC Lifecycle | Process of creating, validating, distributing, and eventually retiring indicators as they lose relevance |
| Defanging | Practice of modifying malicious URLs and domains in reports to prevent accidental clicks (e.g., evil[.]com) |
Tools & Systems
- MISP: Open-source threat intelligence sharing platform for managing, storing, and distributing IOCs
- VirusTotal: Multi-engine malware scanning and threat intelligence platform for IOC enrichment
- OpenCTI: Open-source cyber threat intelligence platform supporting STIX 2.1 natively
- Yeti: Open-source platform for organizing observables, indicators, and TTPs
- CyberChef: GCHQ's data transformation tool useful for decoding, defanging, and formatting IOCs
Common Scenarios
Scenario: Post-Incident IOC Package for ISAC Sharing
Context: After responding to a Qakbot infection that led to Cobalt Strike deployment, the IR team must package all IOCs for sharing with the Financial Services ISAC (FS-ISAC).
Approach:
- Compile all network, host, and email indicators from the investigation
- Enrich each IOC with VirusTotal and MISP correlation data
- Assign confidence scores based on direct observation vs. secondary correlation
- Mark all IOCs with TLP:AMBER for partner sharing
- Export as STIX 2.1 bundle and submit to FS-ISAC TAXII feed
- Create a human-readable IOC summary report for email distribution
Pitfalls:
- Including internal IP addresses or hostnames in shared IOC packages (information leakage)
- Sharing IOCs at TLP:WHITE that should be restricted to TLP:AMBER
- Not defanging URLs and domains in human-readable reports
- Sharing IP addresses of legitimate CDNs or cloud providers as malicious IOCs
Output Format
INDICATOR OF COMPROMISE REPORT
================================
Incident: INC-2025-1547
Date: 2025-11-15
TLP: AMBER
Sharing: FS-ISAC, internal SOC
NETWORK INDICATORS
Type | Value | Confidence | Context
---------|--------------------------|------------|--------
IPv4 | 185.220.101[.]42 | 95 | Qakbot C2 server
IPv4 | 91.215.85[.]17 | 90 | Cobalt Strike C2
Domain | update.evil[.]com | 95 | Staging domain
URL | hxxps://185.220[.]101.42/gate.php | 95 | C2 check-in
JA3 | a0e9f5d64349fb13191bc7...| 80 | Qakbot TLS fingerprint
HOST INDICATORS
Type | Value | Confidence | Context
---------|--------------------------|------------|--------
SHA-256 | a1b2c3d4e5f6... | 100 | Qakbot dropper
SHA-256 | b2c3d4e5f6a7... | 100 | Cobalt Strike beacon
FilePath | C:\Users\*\AppData\Local\Temp\update.exe | 85 | Dropper location
RegKey | HKCU\...\Run\svcupdate | 90 | Persistence
Mutex | Global\MTX_0x1234ABCD | 95 | Qakbot instance lock
Task | WindowsUpdate | 90 | Scheduled task persistence
EMAIL INDICATORS
Type | Value | Confidence | Context
---------|--------------------------|------------|--------
Sender | billing@spoofed[.]com | 95 | Phishing sender
Subject | "Invoice-Nov2025" | 70 | Phishing subject line
Hash | c3d4e5f6a7b8... | 100 | Malicious .docm attachment
TOTAL: 14 indicators | HIGH confidence avg: 91© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 3 other files (scripts, references) in skills/collecting-indicators-of-compromise of mukul975/Anthropic-Cybersecurity-Skills.
- SKILL.md
- LICENSE
- references/api-reference.md
- scripts/agent.py
Open the folder on GitHubat commit 54a7988
Compare with similar skills
Collecting Indicators Of Compromise next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Collecting Indicators Of Compromise this skillmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~2.7k | Automated safety check: Pass | Apache-2.0 | |
| Threat Intelligence OSINTzhaoxuya520/reverse-skill | 41k | 1 repos | ~1k | Automated safety check: Pass | MIT | |
| Enrich Iocdandye/ai-runbooks | 127 | — | ~702 | Automated safety check: Pass | Apache-2.0 | |
| Secops Detection Engineeringgoogle/skills | 21k | 1 repos | ~4.8k | Automated safety check: Pass | Apache-2.0 | |
| Malware Analystaiskillstore/marketplace | 433 | 6 repos | ~1.7k | Automated safety check: Pass | None | |
| Detection Engineering Coverage Evaluationgoogle/skills | 21k | — | ~3.3k | Automated safety check: Pass | Apache-2.0 |
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Questions about Collecting Indicators Of Compromise
What does Collecting Indicators Of Compromise do?
Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Collecting Indicators Of Compromise is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing.
When should I use Collecting Indicators Of Compromise?
Collecting Indicators Of Compromise fits situations like: tasks that involve OSINT; tasks that involve Security operations.
How do I install Collecting Indicators Of Compromise in Claude Code?
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill collecting-indicators-of-compromise -a claude-code`. Or copy the skill folder (skills/collecting-indicators-of-compromise in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/collecting-indicators-of-compromise in your project. Claude Code loads it when a task matches its description.
How do I install Collecting Indicators Of Compromise in Codex?
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill collecting-indicators-of-compromise -a codex`. Or copy the skill folder (skills/collecting-indicators-of-compromise in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/collecting-indicators-of-compromise in your project. Codex loads it when a task matches its description.
Can I use Collecting Indicators Of Compromise in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill collecting-indicators-of-compromise -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/collecting-indicators-of-compromise, .gemini/skills/collecting-indicators-of-compromise, .github/skills/collecting-indicators-of-compromise and .opencode/skills/collecting-indicators-of-compromise in your project.
What does Collecting Indicators Of Compromise need to run?
Going by SKILL.md and its folder, Collecting Indicators Of Compromise needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Collecting Indicators Of Compromise access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Collecting Indicators Of Compromise safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Collecting Indicators Of Compromise use?
Collecting Indicators Of Compromise is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Collecting Indicators Of Compromise use?
About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 558 tokens, read only when the agent opens those files.
What are the alternatives to Collecting Indicators Of Compromise?
Skills that share tags, products or a category with Collecting Indicators Of Compromise: Threat Intelligence OSINT (zhaoxuya520/reverse-skill, 41k stars), Enrich Ioc (dandye/ai-runbooks, 127 stars), Secops Detection Engineering (google/skills, 21k stars) and Malware Analyst (aiskillstore/marketplace, 433 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Collecting Indicators Of Compromise?
mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.
Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.