SKILLEMALL.ai

AC hunt-ldap

Hunt LDAP Injection and XPath Injection — authentication bypass, blind char-by-char attribute exfiltration, AD user/group enumeration, XML-store XPath bypass. Covers the LDAP special-character set (* ( ) \ NUL /), search-filter-context vs DN-injection, parenthesis-balancing, AND/OR filter logic, and {SSHA}/{CRYPT} userPassword exfil on non-AD directories. Use when target uses LDAP/AD authentication, corporate SSO with a directory backend, an address-book/people-search API, or XML-based data stores queried with XPath.

elementalsouls/Claude-BugHunter Agent Skills author: elementalsouls 1 file body ≈ 3 653 tokens Open the sourcegithub.com analyzed 2 h ago

Hunt LDAP Injection and XPath Injection — authentication bypass, blind char-by-char attribute exfiltration, AD user/group enumeration, XML-store XPath bypass.

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

ProcedureSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
99
Quality 40%
82
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Risky intent intent-offensive-security SKILL.md:11
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      > public platforms (most live on internal-pentest reports). This skill is

    Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "sources"
    • note frontmatter-key unknown frontmatter key "report_count"
    • note edit-residue the text marks something as outdated (lines 49): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 62/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 4 mutating operations with no state check
    • 60Failures and branches. 2 branches
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 19 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3653 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 522: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 19 items
    • +4Has examples (8 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.