Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2022-30333PUBLISHED: 2022-05-09RARLAB UnRAR before 6.12 on Linux and UNIX allows directory traversal to write to files during an extract (aka unpack) operation, as demonstrated by creating a ~/.ssh/authorized_keys file. NOTE: WinRAR and Android RAR are unaffected.
CVE-2022-23066PUBLISHED: 2022-05-09
In Solana rBPF versions 0.2.26 and 0.2.27 are affected by Incorrect Calculation which is caused by improper implementation of sdiv instruction. This can lead to the wrong execution path, resulting in huge loss in specific cases. For example, the result of a sdiv instruction may decide whether to tra...
CVE-2022-28463PUBLISHED: 2022-05-08ImageMagick 7.1.0-27 is vulnerable to Buffer Overflow.
CVE-2022-28470PUBLISHED: 2022-05-08marcador package in PyPI 0.1 through 0.13 included a code-execution backdoor.
CVE-2022-1620PUBLISHED: 2022-05-08NULL Pointer Dereference in function vim_regexec_string at regexp.c:2729 in GitHub repository vim/vim prior to 8.2.4901. NULL Pointer Dereference in function vim_regexec_string at regexp.c:2729 allows attackers to cause a denial of service (application crash) via a crafted input.
User Rank: Apprentice
5/19/2015 | 1:36:42 PM
Google cannot protect privacy by definition: as the source of statistics (for gained from texts phrases) Google uses popularity, how popular are the phrases among people that typed the same search queries/ search for the same. Google cannot exist without spying.
However, there is structured data that can search for people - not people for information, but information for people. I discovered and patented how to structure any data: Language has its own Internal parsing, indexing and statistics. For instance, there are two sentences:
a) 'Sam!'
b) 'A loud ringing of one of the bells was followed by the appearance of a
smart chambermaid in the upper sleeping gallery, who, after tapping at
one of the doors, and receiving a request from within, called over the
balustrades -'Sam!'.'
Evidently, that the 'Sam' has different importance into both sentences, in regard to extra information in both. This distinction is reflected as the phrases, which contain 'Sam', weights: the first has 1, the second – 0.08; the greater weight signifies stronger emotional 'acuteness'.
First you need to parse obtaining phrases from clauses, restoring omitted words, for sentences and paragraphs.
Next, you calculate Internal statistics, weights; where the weight refers to the frequency that a phrase occurs in relation to other phrases.
After that data is indexed by common dictionary, like Webster, and annotated by subtexts.
This is a small sample of the structured data:
this - signify - <> : 333333
both - are - once : 333333
confusion - signify - <> : 333321
speaking - done - once : 333112
speaking - was - both : 333109
place - is - in : 250000
To see the validity of technology - pick up any sentence.
Do you have a pencil?
My technology came from Analytic Philosophy, Internal Relations Theory.