Performing Indicator Lifecycle Management

What it does

When your agent uses it

• Maintaining a threat intelligence indicator lifecycle process
• Aging out stale IOCs
• Reducing analyst fatigue from low-quality indicators

Example prompts

• “Use the performing-indicator-lifecycle-management skill to track IOCs through discovery, enrichment/validation (VirusTotal, Shodan, passive DNS)…”
• “/performing-indicator-lifecycle-management”

Requirements

• Python 3

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

1. 1Discovery: IOC first identified from threat intelligence, malware analysis, or incident response
2. 2Validation: IOC verified against enrichment sources (VirusTotal, Shodan)
3. 3Enrichment: Additional context added (WHOIS, passive DNS, threat actor attribution)
4. 4Deployment: IOC pushed to detection systems (SIEM, IDS, firewall)
5. 5Monitoring: Track hit rates, false positive rates, detection efficacy
6. 6Review: Periodic assessment of IOC relevance and accuracy
7. 7Retirement: IOC expired or removed based on aging policy

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 2 files in scripts/ (Python), which the agent can run.

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Links to these hosts (documentation or services it may open):

  • misp-project.org
  • docs.oasis-open.org
  • first.org

  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

Performing Indicator Lifecycle Management loads about 1.5k tokens when it runs, and up to ~2.5k if it reads all its reference files. Until then it costs about 111 tokens; SKILL.md has 343 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~111

When it runs · the whole SKILL.md, loaded when a task matches

~1.5k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~2.5k

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

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). 343 words, ~1,461 tokens.

name

performing-indicator-lifecycle-management

description

Tracks IOCs through discovery, enrichment/validation (VirusTotal, Shodan, passive DNS), deployment to SIEM/IDS watchlists, hit-rate and false-positive monitoring, confidence-score decay, and automated expiration using MISP/OpenCTI and STIX. Use when building or maintaining a threat intelligence indicator lifecycle process, aging out stale IOCs, or reducing analyst fatigue from low-quality indicators.

domain

cybersecurity

subdomain

threat-intelligence

tags

threat-intelligence, cti, ioc, mitre-attack, stix, indicator-lifecycle, ioc-management

version

1.0

author

mahipal

license

Apache-2.0

nist_csf

ID.RA-01, ID.RA-05, DE.CM-01, DE.AE-02

mitre_attack

T1591, T1592, T1593, T1589

from datetime import datetime, timedelta
from enum import Enum

class IOCState(Enum):
    DISCOVERED = "discovered"
    VALIDATED = "validated"
    ENRICHED = "enriched"
    DEPLOYED = "deployed"
    MONITORING = "monitoring"
    UNDER_REVIEW = "under_review"
    RETIRED = "retired"

class IOCLifecycle:
    def __init__(self, ioc_type, value, source, initial_confidence=50):
        self.ioc_type = ioc_type
        self.value = value
        self.source = source
        self.confidence = initial_confidence
        self.state = IOCState.DISCOVERED
        self.created = datetime.utcnow()
        self.last_updated = datetime.utcnow()
        self.last_seen = None
        self.hit_count = 0
        self.false_positive_count = 0
        self.history = [{"state": "discovered", "timestamp": self.created.isoformat()}]

    def transition(self, new_state: IOCState, reason=""):
        self.state = new_state
        self.last_updated = datetime.utcnow()
        self.history.append({
            "state": new_state.value,
            "timestamp": self.last_updated.isoformat(),
            "reason": reason,
        })

    def apply_decay(self):
        """Apply confidence decay based on IOC type half-life."""
        half_lives = {"ip": 30, "domain": 90, "hash": 365, "url": 60}
        half_life = half_lives.get(self.ioc_type, 90)
        age_days = (datetime.utcnow() - self.created).days
        decay_factor = 0.5 ** (age_days / half_life)
        self.confidence = max(0, int(self.confidence * decay_factor))

    def record_hit(self, is_true_positive=True):
        self.hit_count += 1
        self.last_seen = datetime.utcnow()
        if not is_true_positive:
            self.false_positive_count += 1
            if self.false_positive_count > 3:
                self.transition(IOCState.UNDER_REVIEW, "Excessive false positives")

    def should_retire(self):
        max_ages = {"ip": 90, "domain": 180, "hash": 730, "url": 120}
        max_age = max_ages.get(self.ioc_type, 180)
        age_days = (datetime.utcnow() - self.created).days
        return age_days > max_age and self.hit_count == 0

© 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 7 other files (scripts, references, assets) in skills/performing-indicator-lifecycle-management of mukul975/Anthropic-Cybersecurity-Skills.

• SKILL.md
• LICENSE
• assets/template.md
• references/api-reference.md
• references/standards.md
• references/workflows.md
• scripts/agent.py
• scripts/process.py

Open the folder on GitHubat commit 54a7988