vulnerability / NVI-00015408 / Revision 1
asteval Sandbox Escape: arbitrary native memory read/write via numpy ctypes in default asteval Interpreter
GitHub lists this reviewed advisory for asteval. Published version ranges and source prerequisites are shown below; this is not an inspection of a visitor’s application.
This report has not inspected your inventory, configuration, deployed build, reachability or evidence. A catalog listing and a severity score do not establish exposure or compromise.
01 / Meaning
Why it matters
Published affected context helps an owner decide what evidence to gather. This report has not examined your application.
5.5 medium
GitHub source severity; exploitability and local consequence require separate evidence.
As of · GitHub Advisory Database
02 / Applicability
The affected context
Affected versions, configuration prerequisites and known exclusions are public. Confirm each one against the deployed service.
asteval
source listed< 1.0.9
### Summary With its default configuration (numpy enabled, `import` disabled), asteval's `Interpreter` lets an attacker-controlled expression obtain a raw **arbitrary process-memory read and write** primitive, without using `import`, any `__dunder__` attribute, or `eval`/`exec`/`getattr`. Arbitrary in-process read/write is equivalent to arbitrary code execution and is a complete escape of the sandbox whose entire purpose is "untrusted string in, no arbitrary execution out." Any application that feeds untrusted input to asteval with numpy installed (the default) is affected. ### Details asteval's attribute filter (`asteval/astutils.py: safe_getattr`) blocks every `__dunder__` name and blocks objects whose attribute value is *identity-equal* to one of the modules in `UNSAFE_MODULES = {io, os, sys, ctypes}`. The `ctypes` **module** entry was added recently (commit 9d9d430) and correctly blocks `ndarray.ctypes._ctypes`. However, the module check is identity-only against the ctypes *module*. It does not cover ctypes **type objects** and their metaclass methods, which are reachable through numpy's `ndarray.ctypes` wrapper using only ordinary (non-dunder) attribute names: zeros(1,
03 / Response
What to do next
- investigate
Identify the exact component and deployed version, examine the linked publisher’s conditions, and retain evidence of any mitigation.
Confirm current vendor support, compatibility and deployment evidence. This report has not tested a fix in your system. GitHub Advisory Database
A fixed release is not deployment evidence.
Check current vendor support and compatibility. After making a change, verify the deployed build and relevant runtime conditions. Keep the evidence, owner and time. An updated lockfile alone does not prove what is running.
04 / Limits
What this report cannot establish
- Customer inventory, deployment, reachability and exploitation have not been inspected.
05 / Provenance
Sources you can inspect
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- GHSA-9w56-46f6-3qhx ↗
GitHub Advisory Database · vendor advisory
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Public revision history
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- Revision 1 ·
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