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CC detecting-lateral-movement-with-splunk

Detect adversary lateral movement across networks using Splunk SPL queries against Windows authentication logs, SMB traffic, and remote service (WMI/PsExec/RDP) abuse. Use when hunting for MITRE ATT&CK TA0008 lateral movement activity or investigating suspected pivoting between hosts during an incident, with Splunk as the SIEM.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 8 files · 2 scripts body ≈ 929 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Detect adversary lateral movement across networks using Splunk SPL queries against Windows authentication logs, SMB traffic, and remote service…

As a process C 62/100 · Has gaps — weak spots: when it triggers, failures and branches, running it twice

AnalyzerPeople and hiringtype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
80/100
safety, quality, tests
Safety 60%
82
Quality 40%
78
Run on models
none yet
Process rating
C
62/100
Has gaps
Failures and branches w 10
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 18

    ✓ No critical or high findings

    Medium and low: 18
    • low Risky intent intent-offensive-security assets/template.md:1
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      # Lateral Movement Hunt Template
    • low Risky intent intent-offensive-security assets/template.md:23
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ## Lateral Movement Path Map
    • low Risky intent intent-offensive-security references/api-reference.md:1
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      # API Reference: Detecting Lateral Movement with Splunk
      detector
    • low Risky intent intent-offensive-security references/api-reference.md:3
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ## Key Lateral Movement Techniques
    • low Risky intent intent-offensive-security references/standards.md:1
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      # Standards and References - Lateral Movement Detection with Splunk
    • low Risky intent intent-offensive-security references/standards.md:3
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ## MITRE ATT&CK Lateral Movement (TA0008)
    • low Risky intent intent-offensive-security references/standards.md:32
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ## Key Windows Event IDs for Lateral Movement
    • low Risky intent intent-offensive-security references/standards.md:58
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | Protocol | Lateral Movement | Event Indicators |
    • low Risky intent intent-offensive-security references/workflows.md:1
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      # Detailed Hunting Workflow - Lateral Movement with Splunk
    • low Risky intent intent-offensive-security references/workflows.md:50
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ## Phase 3: Service-Based Lateral Movement
    • low Risky intent intent-offensive-security references/workflows.md:71
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ## Phase 4: WMI and DCOM Lateral Movement
    • low Risky intent intent-offensive-security references/workflows.md:80
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ### Step 4.2 - DCOM Lateral Movement
    • low Risky intent intent-offensive-security references/workflows.md:90
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ### Step 5.1 - Build Lateral Movement Graph
    • low Risky intent intent-offensive-security SKILL.md:3
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      description: Detect adversary lateral movement across networks using Splunk SPL queries
      detector
    • low Risky intent intent-offensive-security SKILL.md:5
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      abuse. Use when hunting for MITRE ATT&CK TA0008 lateral movement activity or investigating
    • low Risky intent intent-offensive-security SKILL.md:39
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      # Detecting Lateral Movement with Splunk
      detector
    • low Risky intent intent-offensive-security SKILL.md:47
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - When proactively hunting for TA0008 (Lateral Movement) techniques
    • low Risky intent intent-offensive-security SKILL.md:59
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      1. **Define Lateral Movement Scope**: Identify which lateral movement techniques to hunt (RDP, SMB/Admin Shares, WinRM, PsExec, WMI, DCOM, SSH).

    Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "domain"
    • note frontmatter-key unknown frontmatter key "subdomain"
    • note frontmatter-key unknown frontmatter key "d3fend_techniques"
    • note frontmatter-key unknown frontmatter key "nist_csf"
    • note frontmatter-key unknown frontmatter key "mitre_attack"

    Process rating: all ten parameters 62/100

    • 0Failures and branches. Linear process with no failure handling
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 22 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 929 tokens
    • 100Progress reporting. Reports progress

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • -43 reference files, but SKILL.md never points to them: the model will not open them
    • -32 of 2 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 329: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 22 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.