GHSA-GGWJ-625Q-9WGF
Vulnerability from github – Published: 2022-05-14 02:53 – Updated: 2022-05-14 02:53
VLAI
Details
RICOS in IBM Algo Credit Limits (aka ACLM) 4.5.0 through 4.7.0 before 4.7.0.03 FP5 in IBM Algorithmics allows remote attackers to obtain potentially sensitive Tomcat stack-trace information via non-printing characters in a cookie to the /classes/ URI, as demonstrated by the \x00 character.
{
"affected": [],
"aliases": [
"CVE-2014-0871"
],
"database_specific": {
"cwe_ids": [
"CWE-200"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2014-07-07T11:01:00Z",
"severity": "MODERATE"
},
"details": "RICOS in IBM Algo Credit Limits (aka ACLM) 4.5.0 through 4.7.0 before 4.7.0.03 FP5 in IBM Algorithmics allows remote attackers to obtain potentially sensitive Tomcat stack-trace information via non-printing characters in a cookie to the /classes/ URI, as demonstrated by the \\x00 character.",
"id": "GHSA-ggwj-625q-9wgf",
"modified": "2022-05-14T02:53:40Z",
"published": "2022-05-14T02:53:40Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2014-0871"
},
{
"type": "WEB",
"url": "https://exchange.xforce.ibmcloud.com/vulnerabilities/90945"
},
{
"type": "WEB",
"url": "https://www.sec-consult.com/fxdata/seccons/prod/temedia/advisories_txt/20140630-0_IBM_Algorithmics_RICOS_multiple_vulnerabilities_v10.txt"
},
{
"type": "WEB",
"url": "http://packetstormsecurity.com/files/127304/IBM-Algorithmics-RICOS-Disclosure-XSS-CSRF.html"
},
{
"type": "WEB",
"url": "http://seclists.org/fulldisclosure/2014/Jun/173"
},
{
"type": "WEB",
"url": "http://secunia.com/advisories/59296"
},
{
"type": "WEB",
"url": "http://www-01.ibm.com/support/docview.wss?uid=swg21675881"
},
{
"type": "WEB",
"url": "http://www.securityfocus.com/archive/1/532598/100/0/threaded"
}
],
"schema_version": "1.4.0",
"severity": []
}
Loading…
Loading…
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.
Loading…
Loading…