FKIE_CVE-2026-97863
Vulnerability from fkie_nvd - Published: 2026-09-25 09:17 - Updated: 2026-09-25 14:31
Severity
Summary
The cisco_firesight_manager_ACL_rule_export module in misp-modules generates a shell script (.sh) that authenticates to and calls the Cisco fireSIGHT Manager API. The module interpolates configuration values (IP address, login, password, domain ID, policy ID) and MISP attribute values (destination IPs, URLs, event info comments) directly into single-quoted shell string assignments without any escaping or sanitization. Because the values are placed inside single-quoted shell strings, any value containing a single-quote character (e.g., a crafted ip-dst or url attribute value submitted to MISP) breaks out of the quoting context, allowing an attacker to inject arbitrary shell commands into the exported script. A security analyst who subsequently executes the generated .sh file unmodified would run the injected commands with their own privileges, potentially exposing fireSIGHT Manager credentials, modifying ACL rules, or compromising the analyst workstation. Additionally, the module contained a secondary defect where the variable 'config' was only assigned inside a conditional block but referenced unconditionally afterward, causing a NameError (denial of service) when the request payload lacked a 'config' key. The vulnerability requires the attacker to have the ability to submit MISP events or attributes containing a single-quote character and the victim to execute the exported script. No authentication bypass is required beyond standard MISP event-submission privileges.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"collectionURL": "https://github.com/MISP/misp-modules",
"defaultStatus": "unaffected",
"modules": [
"cisco_firesight_manager_ACL_rule_export"
],
"product": "misp-modules",
"programFiles": [
"misp_modules/modules/export_mod/cisco_firesight_manager_ACL_rule_export.py"
],
"repo": "https://github.com/misp/misp-modules",
"vendor": "misp",
"versions": [
{
"lessThanOrEqual": "3.0.10",
"status": "affected",
"version": "0",
"versionType": "semver"
}
]
}
],
"source": "5a6e4751-2f3f-4070-9419-94fb35b644e8"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "The cisco_firesight_manager_ACL_rule_export module in misp-modules generates a shell script (.sh) that authenticates to and calls the Cisco fireSIGHT Manager API. The module interpolates configuration values (IP address, login, password, domain ID, policy ID) and MISP attribute values (destination IPs, URLs, event info comments) directly into single-quoted shell string assignments without any escaping or sanitization. Because the values are placed inside single-quoted shell strings, any value containing a single-quote character (e.g., a crafted ip-dst or url attribute value submitted to MISP) breaks out of the quoting context, allowing an attacker to inject arbitrary shell commands into the exported script. A security analyst who subsequently executes the generated .sh file unmodified would run the injected commands with their own privileges, potentially exposing fireSIGHT Manager credentials, modifying ACL rules, or compromising the analyst workstation. Additionally, the module contained a secondary defect where the variable \u0027config\u0027 was only assigned inside a conditional block but referenced unconditionally afterward, causing a NameError (denial of service) when the request payload lacked a \u0027config\u0027 key. The vulnerability requires the attacker to have the ability to submit MISP events or attributes containing a single-quote character and the victim to execute the exported script. No authentication bypass is required beyond standard MISP event-submission privileges."
}
],
"id": "CVE-2026-97863",
"lastModified": "2026-09-25T14:31:45.000",
"metrics": {
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "NONE",
"attackVector": "NETWORK",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 6.3,
"baseSeverity": "MEDIUM",
"confidentialityRequirement": "NOT_DEFINED",
"exploitMaturity": "NOT_DEFINED",
"integrityRequirement": "NOT_DEFINED",
"modifiedAttackComplexity": "NOT_DEFINED",
"modifiedAttackRequirements": "NOT_DEFINED",
"modifiedAttackVector": "NOT_DEFINED",
"modifiedPrivilegesRequired": "NOT_DEFINED",
"modifiedSubAvailabilityImpact": "NOT_DEFINED",
"modifiedSubConfidentialityImpact": "NOT_DEFINED",
"modifiedSubIntegrityImpact": "NOT_DEFINED",
"modifiedUserInteraction": "NOT_DEFINED",
"modifiedVulnAvailabilityImpact": "NOT_DEFINED",
"modifiedVulnConfidentialityImpact": "NOT_DEFINED",
"modifiedVulnIntegrityImpact": "NOT_DEFINED",
"privilegesRequired": "LOW",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "HIGH",
"subConfidentialityImpact": "HIGH",
"subIntegrityImpact": "HIGH",
"userInteraction": "ACTIVE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:A/VC:N/VI:N/VA:N/SC:H/SI:H/SA:H/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",
"version": "4.0",
"vulnAvailabilityImpact": "NONE",
"vulnConfidentialityImpact": "NONE",
"vulnIntegrityImpact": "NONE",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "5a6e4751-2f3f-4070-9419-94fb35b644e8",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-97863",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-09-25T13:18:10.409406Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-09-25T09:17:08.003",
"references": [
{
"source": "5a6e4751-2f3f-4070-9419-94fb35b644e8",
"url": "https://github.com/misp/misp-modules/commit/625b54908efbd6acc8343aa3370d401dd370e748"
}
],
"sourceIdentifier": "5a6e4751-2f3f-4070-9419-94fb35b644e8",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-78"
}
],
"source": "5a6e4751-2f3f-4070-9419-94fb35b644e8",
"type": "Secondary"
}
]
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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