Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2022-43762PUBLISHED: 2023-02-08Lack of verification in B&R APROL Tbase server versions < R 4.2-07 may lead to memory leaks when receiving messages
CVE-2022-43763PUBLISHED: 2023-02-08Insufficient check of preconditions could lead to Denial of Service conditions when calling commands on the Tbase server of B&R APROL versions < R 4.2-07.
CVE-2022-43764PUBLISHED: 2023-02-08Insufficient validation of input parameters when changing configuration on Tbase server in B&R APROL versions < R 4.2-07 could result in buffer overflow. This may lead to Denial-of-Service conditions or execution of arbitrary code.
CVE-2022-43765PUBLISHED: 2023-02-08B&R APROL versions < R 4.2-07 doesn’t process correctly specially formatted data packages sent to port 55502/tcp, which may allow a network based attacker to cause an application Denial-of-Service.
CVE-2022-2094PUBLISHED: 2023-02-08The Yellow Yard Searchbar WordPress plugin before 2.8.2 does not escape some URL parameters before outputting them back to the user, leading to Reflected Cross-Site Scripting
User Rank: Author
9/29/2014 | 4:58:39 PM
creating the core, shared data model as ive described above (and storing data in it, analyzing it) is just the beginning. it isnt even necesary to look outside for a formal framework. in fact, just adding key fields and relationships to related data sets can be even more effective in an in-house solution that, for example, groups types of malware with simple, high-level incident reponse and triage procedures to serve as first-pass recipe system for moving out quickly when new malware beomes active malware.
we have seen big successes where organizations begin to track types of as-yet-unseen malware in and aorund them be able to react more quicky with mitigation by also tracking (simply, of course) what has been done in the past for similar problems. we use a simple "Polarity" metric attached to all our Actor-Target-Effect-Practice tuples, if you will, that map positive, negative or neutral to things like "security research" or "security solution" (as seen here).
this allows for quick sorting and filtering data to isolate things that may be not be active yet or may be the solution side of a problem you didnt yet know you have. what's more, it makes it easy to matrix these items into exploit knowledge bases or in-house incident respone recipes too. it's also great for surfacing to management in a way that tells them what may be out there too and show quantitatively what portion of your strategy these kinds of things occupy. simple data models can be very powerful when extended the right way and when data is collected diligently. not always a need to look outside for a solution either.