DataFlowSanitizer
E292718
DataFlowSanitizer is an LLVM-based dynamic data flow analysis tool used to track and detect the propagation of untrusted or tainted data at runtime.
All labels observed (1)
| Label | Occurrences |
|---|---|
| DataFlowSanitizer canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T2716461 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DataFlowSanitizer Context triple: [LLVM, hasComponent, DataFlowSanitizer]
-
A.
Checkmarx
Checkmarx is a cybersecurity company specializing in application security testing solutions that help organizations identify and remediate vulnerabilities in their software code.
-
B.
NetFlow
NetFlow is a network protocol developed by Cisco for collecting and analyzing IP traffic flow data to support monitoring, accounting, and security.
-
C.
Security Analysis
Security Analysis is a foundational investing book by Benjamin Graham (with David Dodd) that established the principles of value investing and rigorous financial statement analysis.
-
D.
XProtect
XProtect is a video management software platform widely used for managing and recording IP-based surveillance systems.
-
E.
Continuous Diagnostics and Mitigation tools
Continuous Diagnostics and Mitigation tools are cybersecurity solutions that provide ongoing monitoring, vulnerability management, and risk assessment to help organizations strengthen and maintain their security posture.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DataFlowSanitizer Target entity description: DataFlowSanitizer is an LLVM-based dynamic data flow analysis tool used to track and detect the propagation of untrusted or tainted data at runtime.
-
A.
Checkmarx
Checkmarx is a cybersecurity company specializing in application security testing solutions that help organizations identify and remediate vulnerabilities in their software code.
-
B.
NetFlow
NetFlow is a network protocol developed by Cisco for collecting and analyzing IP traffic flow data to support monitoring, accounting, and security.
-
C.
Security Analysis
Security Analysis is a foundational investing book by Benjamin Graham (with David Dodd) that established the principles of value investing and rigorous financial statement analysis.
-
D.
XProtect
XProtect is a video management software platform widely used for managing and recording IP-based surveillance systems.
-
E.
Continuous Diagnostics and Mitigation tools
Continuous Diagnostics and Mitigation tools are cybersecurity solutions that provide ongoing monitoring, vulnerability management, and risk assessment to help organizations strengthen and maintain their security posture.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
LLVM sanitizer
ⓘ
dynamic data flow analysis tool ⓘ taint analysis tool ⓘ |
| analysisType | dynamic analysis ⓘ |
| approach | shadow memory for taint metadata ⓘ |
| basedOn | LLVM ⓘ |
| category |
program analysis tool
ⓘ
security analysis tool ⓘ software testing tool ⓘ |
| configuration |
taint labels for data sinks
ⓘ
taint labels for data sources ⓘ |
| detects |
improper propagation of untrusted data
ⓘ
tainted data reaching sensitive sinks ⓘ |
| developedBy |
LLVM
ⓘ
surface form:
LLVM project
|
| documentation | LLVM sanitizer documentation ⓘ |
| focus | security-related data flow properties ⓘ |
| goal |
enforce data flow policies at runtime
ⓘ
help developers find security issues related to untrusted data ⓘ |
| granularity | byte-level taint tracking ⓘ |
| implements | dynamic data flow analysis ⓘ |
| instrumentationType | compile-time instrumentation ⓘ |
| integratedInto |
Clang
ⓘ
LLVM ⓘ
surface form:
LLVM compiler toolchain
|
| license | open source ⓘ |
| limitation |
requires source-level or build-system changes
ⓘ
runtime performance overhead ⓘ |
| monitors |
data flows between memory locations
ⓘ
data flows between program variables ⓘ |
| operatesAt | runtime ⓘ |
| platform |
Linux
ⓘ
Unix-like systems ⓘ |
| relatedTo |
AddressSanitizer
ⓘ
MemorySanitizer ⓘ ThreadSanitizer ⓘ |
| requires |
compilation with Clang/LLVM
ⓘ
recompilation of target program ⓘ |
| supports |
multiple taint sinks
ⓘ
multiple taint sources ⓘ taint tracking ⓘ user-defined taint labels ⓘ |
| target |
C programs
ⓘ
C++ programs ⓘ |
| tracks |
propagation of tainted data
ⓘ
propagation of untrusted data ⓘ |
| useCase |
detecting use of untrusted inputs
ⓘ
information flow tracking ⓘ security analysis ⓘ vulnerability detection ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: DataFlowSanitizer Description of subject: DataFlowSanitizer is an LLVM-based dynamic data flow analysis tool used to track and detect the propagation of untrusted or tainted data at runtime.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.