Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2022-48161PUBLISHED: 2023-02-01Easy Images v2.0 was discovered to contain an arbitrary file download vulnerability via the component /application/down.php. This vulnerability is exploited via a crafted GET request.
CVE-2023-0341PUBLISHED: 2023-02-01
A stack buffer overflow exists in the ec_glob function of editorconfig-core-c before v0.12.6 which allowed an attacker to arbitrarily write to the stack and possibly allows remote code execution. editorconfig-core-c v0.12.6 resolved this vulnerability by bound checking all write operations over the ...
CVE-2023-23924PUBLISHED: 2023-02-01
Dompdf is an HTML to PDF converter. The URI validation on dompdf 2.0.1 can be bypassed on SVG parsing by passing `<image>` tags with uppercase letters. This may lead to arbitrary object unserialize on PHP < 8, through the `phar` URL wrapper. An attacker can exploit the vulnerability to call...
CVE-2023-24241PUBLISHED: 2023-02-01Forget Heart Message Box v1.1 was discovered to contain a SQL injection vulnerability via the name parameter at /admin/loginpost.php.
CVE-2023-24956PUBLISHED: 2023-02-01Forget Heart Message Box v1.1 was discovered to contain a SQL injection vulnerability via the name parameter at /cha.php.
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.