PyTorch Tuple torch.ops.profiler._call_end_callbacks_on_jit_fut memory corruption
A vulnerability was found in PyTorch 2.6.0+cu124. It has been declared as critical. Affected by this vulnerability is the function torch.ops.profiler._call_end_callbacks_on_jit_fut of the component Tuple Handler. The manipulation of the argument None leads to memory corruption. The attack can be launched remotely. The complexity of an attack is rather high. The exploitation appears to be difficult.
- Published
- Mar 10, 2025
- Updated
- Jun 17, 2026
- EPSS
- 0.4% · 36th percentile
- CWE
- CWE-119
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Report tools
Action score
9
Monitor
Low priority for now.
- CVSS
- 9 / 40 · 2.3 / 10
- CISA KEV
- 0 / 30 · Not listed
- EPSS
- 0 / 30 · 0.4%
CISA SSVC decision
- Exploitation
- proof of concept
- Automatable
- no
- Technical impact
- partial
Vulnrichment: CISA's decision-tree inputs.
CNA vs NVD score
- NVD
- —
- CNA · VulDB
- 2.3
- NVD has not scored this yet; the score shown is the CNA’s.
CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:P/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N
The score given by the assigning authority versus NVD’s independent score. A gap means the severity is contested.
Noroxi analysis
No Noroxi analysis for this record yet
We don't hand-write analysis for the hundreds of thousands of vulnerabilities in the database; that wouldn't be honest. For notable, high-impact vulnerabilities our team writes the mechanism, detection and remediation steps.
We use this product, ask for helpAffected systems
| Vendor | Product | CPE |
|---|---|---|
| linuxfoundation | pytorch | cpe:2.3:a:linuxfoundation:pytorch |
Affected versions
NVD version ranges (for catalog products). Add the product to your stack with a version and matching uses these.
- linuxfoundation pytorch2.6.0
Versions reported by the vendor
Affected version ranges reported by the assigning authority (VulDB). Independent of NVD's CPE analysis and usually ahead of it.
n/a PyTorch
- 2.6.0+cu124affected
Package-level exposure
OSV and GitHub Advisory data: ecosystem, package and range. SBOM matching uses this table.
| Ecosystem | Package | Affected range | Fix |
|---|---|---|---|
| Debian:12 | pytorch | all versions | — |
| PyPI | torch | up to and including 2.6.0 | — |
| PyPI | torch | up to and including 2.6.0-cu124 | — |
Same product
linuxfoundation: all recordsOther highest-scoring records for the same primary product.
- CVE-2024-48063In PyTorch <=2.4.1, the RemoteModule has Deserialization RCE.39Monitor
- CVE-2022-45907In PyTorch before trunk/89695, torch.jit.annotations.parse_type_line can cause arbitrary code execution because eval is used unsafely.39Monitor
- CVE-2025-32434PyTorch: `torch.load` with `weights_only=True` leads to remote code execution38Monitor
- CVE-2026-24747PyTorch Vulnerable to Remote Code Execution via Untrusted Checkpoint Files35Monitor
- CVE-2024-31583Pytorch before version v2.2.0 was discovered to contain a use-after-free vulnerability in torch/csrc/jit/mobile/interpreter.cpp.31Monitor
- CVE-2025-55560An issue in pytorch v2.7.0 can lead to a Denial of Service (DoS) when a PyTorch model consists of torch.Tensor.to_sparse() and torch.Tensor.30Monitor
Remediation
Which version to upgrade to
Fix versions compiled from the vendor, package registries and Microsoft. Verify the vendor's note before upgrading.
No fix version is recorded for this entry. Check the references for vendor advisories.
Exploit status
No known public exploit
No public exploit has been observed yet. That doesn't mean you're safe, only that the bar is a little higher.
Research context
For pentesters and researchers: attack profile, score disagreement, timeline, patch commits, credits, variant and chain candidates, bug bounty scope. All derived from existing data; no exploit code.
Timeline
From publication to today: proof of concept, Metasploit module, CISA KEV and fix record. Dates are as reported by the sources.
No dated events beyond publication.
FIRST EPSS daily score; only changes of 0.01 or more are recorded (step chart).
Patch and commit links
Commit, PR and diff links among the references. A starting point for patch-diffing and variant hunting; fixes, not exploits.
No commit or PR link among the references.
Credits
All researchersFinders, reporters and analysts named in the CNA record. Click a name for that researcher’s other records.
- Default436352 (VulDB User)reporter
Variant candidates
Same product, same weakness class, within 18 months. If the patch missed the root cause, the sibling bug is here.
- CVE-2025-299821 days apartPyTorch torch.nn.utils.rnn.pad_packed_sequence memory corruption19Monitor
- CVE-2025-299921 days apartPyTorch torch.nn.utils.rnn.unpack_sequence memory corruption19Monitor
- CVE-2025-300021 days apartPyTorch torch.jit.script memory corruption19Monitor
- CVE-2025-300121 days apartPyTorch torch.lstm_cell memory corruption19Monitor
- CVE-2025-312123 days apartPyTorch torch.jit.jit_module_from_flatbuffer memory corruption19Monitor
- CVE-2025-313624 days apartPyTorch CUDACachingAllocator.cpp torch.cuda.memory.caching_allocator_delete memory corruption19Monitor
Chain candidates
An authentication bypass and a privilege-requiring bug in the same product, published close together: combined they may become an unauthenticated path.
—
Bug bounty scope
No known public program.
Source: bounty-targets-data (public HackerOne, Bugcrowd, Intigriti, YesWeHack listings).
Technical details
Attack conditions
- Anyone who can reach it over the internet can trigger it.
- No account or password is required.
- Special conditions such as timing or configuration are required.
If successful
- Confidentiality
- Integrity
- Availability
- Attack vector
- Network
- Attack complexity
- High
- Privileges required
- None
- User interaction
- P
- Scope
- X
Weakness class (CWE)
CWE-119 · Improper Restriction of Operations within the Bounds of a Memory BufferCVSS vector
CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:P/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
nvd-secondary
Attack context
MITRE CAPEC attack patterns and ATT&CK techniques for this weakness class (CWE). A starting point for detection rules and threat hunting.
Attack patterns (CAPEC)
- Buffer Overflow via Environment VariablesCAPEC-10likelihood: High · High
- Overflow BuffersCAPEC-100likelihood: High · Very High
- Buffer ManipulationCAPEC-123likelihood: High · Very High
- Client-side Injection-induced Buffer OverflowCAPEC-14likelihood: Medium · High
- Filter Failure through Buffer OverflowCAPEC-24likelihood: High · High
- MIME ConversionCAPEC-42likelihood: High · High
- Overflow Binary Resource FileCAPEC-44likelihood: High · Very High
- Buffer Overflow via Symbolic LinksCAPEC-45likelihood: High · High
ATT&CK techniques
—
Change log
No changes recorded on tracked fields yet. Score, KEV, exploit maturity and fix status changes appear here.
References
- github.com/pytorch/pytorch/issues/147722
- vuldb.com/?ctiid.299059
- vuldb.com/?id.299059
- vuldb.com/?submit.505959
Vendor advisories and official records. Exploit/PoC links are deliberately left out.