Security audit
Security checks for vulnerabilities and agentic risk
This is a local DWS SQL linting skill with no network, credential, persistence, or destructive behavior, though its documentation overstates check coverage.
Install only if you want an offline, local DWS SQL advisory checker. Do not treat a clean report as proof of complete SQL safety, compliance, performance, or production readiness, especially for generic SQL audit or optimization requests.
The skill makes strong claims about comprehensive syntax, specification, naming, and grammar validation, but the finding indicates the implementation likely does not deliver that coverage. This can create a false sense of assurance: users may trust 'passed' results for SQL safety, compliance, or correctness when important checks are actually missing, leading to unsafe or noncompliant SQL being approved.
Referenced artifact was not completely inspected
| [Keywords](rules/keywords.py) | 594 DWS SQL keyword definitions |
Referenced artifact was not completely inspected
| [Grammar Rules](rules/grammar_rules.py) | 160+ statement type grammar definitions |
Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.
return node
# ============================================================
# DELETE Statement Parser
# ============================================================
def _parse_delete(self):
Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.
# ============================================================
def _parse_delete(self):
"""Parse DELETE statement"""
node = ASTNode("DeleteStmt")
start_token = self._current()
YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).
action_tokens.append(self._advance())
node.children["actions"] = self._tokens_to_text(action_tokens).strip()
node.tokens = [start_token]
node.raw_text = self._get_raw_text(start_token)
return node
# ============================================================
# DROP Parser
# ============================================================
def _parse_drop(self):
"""Parse DROP statement"""
node = ASTNode("DropStmt")
start_token = self._current()
self._advance() # skip DROP
# Object type
obj_types = ["TABLE", "INDEX", "VIEW", "SEQUENCE", "SCHEMA", "DATABASE",
"FUNCTION", "PROCEDURE", "TRIGGER", "TYPE", "DOMAIN", "ROLE",
"USER", "GROUP", "TABLESPACE", "EXTENSION", "FOREIGN",
"SYNONYM", "MATERIALIZED", "NODE", "OUTLINE", "DIRECTORY",
"PUBLICATION", "SUBSCRIPTION", "RESOURCE", "WORKLOAD"]
obj_type = None
Without declared permissions the skill's intent is opaque and cannot be validated.
Overly broad trigger phrases like general SQL review/audit terms can cause the skill to activate for requests outside its real capability boundary. In combination with the claimed comprehensive checking, this increases the chance the agent will inappropriately handle broad SQL security, optimization, or audit tasks and return incomplete or misleading guidance.
This manifest-style YAML contains all human-readable names, descriptions, and fix suggestions in Chinese, which imposes a specific language/locale on users. The file does not offer any language choice or document that the skill is intentionally limited to a Chinese-speaking or region-specific environment.
This YAML file defines all rule names, descriptions, check logic, and fix suggestions exclusively in Chinese, which imposes a specific language on users of the skill. The file does not document that the skill is intended only for a Chinese-speaking or region-specific environment, nor does it offer any language choice.
This code embeds natural-language rule names and categories in Chinese and later renders them directly in reports, making the skill effectively enforce a specific language. The file does not provide an opt-in, fallback, or justification that the tool is intentionally limited to a Chinese-language audience.
No suspicious patterns detected.