AddressSanitizer
E292715
AddressSanitizer is a fast memory error detector that instruments programs to find issues like buffer overflows and use-after-free bugs at runtime.
All labels observed (1)
| Label | Occurrences |
|---|---|
| AddressSanitizer canonical | 6 |
How this entity was disambiguated
This entity first appeared as the object of triple T2716457 — 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: AddressSanitizer Context triple: [LLVM, hasComponent, AddressSanitizer]
-
A.
LLDB
LLDB is a modern, high-performance debugger primarily used with the LLVM toolchain for languages like C, C++, and Objective-C.
-
B.
Kernel Self Protection Project
The Kernel Self Protection Project is a security-focused initiative aimed at hardening the Linux kernel against vulnerabilities and exploitation through proactive defensive features and development practices.
-
C.
Clang-Tidy
Clang-Tidy is a C++ “linter” and static analysis tool that automatically detects and suggests fixes for common programming errors, style issues, and potential bugs in code.
-
D.
Itanium C++ ABI
The Itanium C++ ABI is a widely adopted application binary interface specification that standardizes C++ object layout, name mangling, and calling conventions across many non-Windows platforms and compilers.
-
E.
AppArmor
AppArmor is a Linux kernel security module that confines programs to a limited set of resources using per-application security profiles to reduce the impact of vulnerabilities and attacks.
- 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: AddressSanitizer Target entity description: AddressSanitizer is a fast memory error detector that instruments programs to find issues like buffer overflows and use-after-free bugs at runtime.
-
A.
LLDB
LLDB is a modern, high-performance debugger primarily used with the LLVM toolchain for languages like C, C++, and Objective-C.
-
B.
Kernel Self Protection Project
The Kernel Self Protection Project is a security-focused initiative aimed at hardening the Linux kernel against vulnerabilities and exploitation through proactive defensive features and development practices.
-
C.
Clang-Tidy
Clang-Tidy is a C++ “linter” and static analysis tool that automatically detects and suggests fixes for common programming errors, style issues, and potential bugs in code.
-
D.
Itanium C++ ABI
The Itanium C++ ABI is a widely adopted application binary interface specification that standardizes C++ object layout, name mangling, and calling conventions across many non-Windows platforms and compilers.
-
E.
AppArmor
AppArmor is a Linux kernel security module that confines programs to a limited set of resources using per-application security profiles to reduce the impact of vulnerabilities and attacks.
- F. None of above. chosen
Statements (51)
| Predicate | Object |
|---|---|
| instanceOf |
dynamic analysis tool
ⓘ
memory error detector ⓘ runtime instrumentation tool ⓘ |
| configuration | ASAN_OPTIONS environment variable ⓘ |
| detects |
buffer overflow
ⓘ
double-free ⓘ global buffer overflow ⓘ heap buffer overflow ⓘ invalid free ⓘ memory leaks (with LeakSanitizer integration) ⓘ stack buffer overflow ⓘ stack-use-after-scope (in some configurations) ⓘ use-after-free ⓘ use-after-return ⓘ |
| developedBy | Google ⓘ |
| goal | find memory errors in C and C++ programs ⓘ |
| hasComponent |
compiler instrumentation passes
ⓘ
runtime library ⓘ |
| introducedIn | LLVM 3.1 (initial integration timeframe) ⓘ |
| invocationFlag |
-fsanitize=address (Clang)
ⓘ
-fsanitize=address (GCC) ⓘ |
| license |
Apache License 2.0 with LLVM exceptions
ⓘ
surface form:
Apache License 2.0 (via LLVM)
|
| limitation |
does not detect all uninitialized memory reads
ⓘ
requires recompilation of the program with sanitizer flags ⓘ |
| partOf |
LLVM
ⓘ
surface form:
LLVM project
|
| programmingLanguage |
C
ⓘ
C++ ⓘ Objective-C ⓘ Objective-C++ ⓘ |
| property | low runtime overhead compared to other memory checkers ⓘ |
| relatedTo |
LeakSanitizer
ⓘ
MemorySanitizer ⓘ ThreadSanitizer ⓘ |
| reports |
detailed error messages with stack traces
ⓘ
location of invalid memory access ⓘ type of memory error ⓘ |
| runsAt | runtime ⓘ |
| supportedBy |
Clang
ⓘ
GNU Compiler Collection ⓘ
surface form:
GCC
|
| supportsPlatform |
Android NDK
ⓘ
surface form:
Android (via NDK/Clang)
Linux ⓘ Windows (via ports such as MinGW and Cygwin) ⓘ
surface form:
Windows (via Clang/LLVM)
macOS ⓘ |
| typicalOverhead |
about 2x memory usage
ⓘ
about 2x runtime slowdown (approximate) ⓘ |
| usedFor |
debugging memory corruption bugs
ⓘ
hardening software during testing ⓘ |
| usesTechnique |
compiler-based instrumentation
ⓘ
poisoning and unpoisoning memory regions ⓘ red zones around objects ⓘ shadow memory ⓘ |
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: AddressSanitizer Description of subject: AddressSanitizer is a fast memory error detector that instruments programs to find issues like buffer overflows and use-after-free bugs at runtime.
Referenced by (6)
Full triples — surface form annotated when it differs from this entity's canonical label.