Tools to analyze if the URL is suspicious/Malicious?

What are the tools that a cyber security analyst needs to analyze the URL to determine if it is a suspicious/Malicious one.

microsoft outlook – How to analyze why an email was misdirected?

I received an email from someone I know and relating to a club we both belong to so I’m confident it is not harmful, but in my limited knowledge of email headers I can’t tell why I received it as it was addressed to an email address at a totally different domain.

Although it has the header To: <txxxxx@mweb.co.za> it also has the header Delivered-To: sxxxx.cxxxx@gmail.com and I can’t see any other header that might explain what happened.

Can anyone that understands email headers better than myself explain why this happened? The full headers are included below with the addressee’s address anonymized as txxxxx@mweb.co.za, the sender’s address anonymized as fxxxxxxxxxx@gmail.com and my address anonymized as sxxxx.cxxxx@gmail.com

Delivered-To: sxxxx.cxxxx@gmail.com
Received: by 2002:a17:906:abd4:0:0:0:0 with SMTP id kq20csp1522444ejb;
        Fri, 9 Apr 2021 05:35:43 -0700 (PDT)
X-Received: by 2002:a05:6402:c1:: with SMTP id i1mr17154183edu.315.1617971743566;
        Fri, 09 Apr 2021 05:35:43 -0700 (PDT)
ARC-Seal: i=1; a=rsa-sha256; t=1617971743; cv=none;
        d=google.com; s=arc-20160816;
        b=FVqs1EahnvRbvt8FFZFCIaBPua/RxcD92oDKxkHvqL3qOqIGnXIlbcoS87paleT0/8
         T1v5krVU+YFsvY4mnI7YbYc4yvESCB8vNbr0XkWBnYg7GY/M+J02O/AcZWLoco0jaGhs
         mzassYUpBj/EQfhnRKk1ozVO05QraQ87QeoR3IAopyj5+10a8u/VkYPuPUjMIub/Hn2G
         Fq7x616k0cnh/nx51ADn/xzFKYJZrw4BN+7PCL3tXSb75syoBsjUEQjvAnenySutWSz7
         rAoaMHZvdZxRCnrdNntVpCqe9REPjH8QpvivhpEwI6gnh6AHWUU/Dv6kYLTjx5aPNQfM
         0gPw==
ARC-Message-Signature: i=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=arc-20160816;
        h=content-language:thread-index:mime-version:message-id:date:subject
         :to:from:dkim-signature;
        bh=pdk79xbDyHvYq5L6e08DBSeYp6uMJLfGyugTatCUinQ=;
        b=W636jT76Jenx0BNTx1cySmTP3W5fKAvN2lD2cD7yk1ZZsEsN3KV02HUZdzsPksS5Nb
         XUvazAmCZn9gsVeVNB4N5EJiRsrE8fkS6ODUJT2ymxmqWtujvRiGgS3OE5o08YYpWDTw
         re6DqyblICp8WgGoeqoCdvsNqNGNoOtG+6igvVM8MDVjBCkL2BcHxGbS/xvNmYHVHlJq
         XfwpZ6poKcU/rJeYbaxEwW9gupDyl/ruVBIXSGYVXFv4KlSQ/J0JbW7P+ptBmzxwtg0Y
         7yoko/mcPRiwuRv5wO435vCsTqI9+IP4g5+Rot7vZn7cw9hsk+/ifFeBP+lrp86RAJI4
         ZYGw==
ARC-Authentication-Results: i=1; mx.google.com;
       dkim=pass header.i=@gmail.com header.s=20161025 header.b=e72Bz8nw;
       spf=pass (google.com: domain of fxxxxxxxxxx@gmail.com designates 209.85.220.41 as permitted sender) smtp.mailfrom=fxxxxxxxxxx@gmail.com;
       dmarc=pass (p=NONE sp=QUARANTINE dis=NONE) header.from=gmail.com
Return-Path: <fxxxxxxxxxx@gmail.com>
Received: from mail-sor-f41.google.com (mail-sor-f41.google.com. (209.85.220.41))
        by mx.google.com with SMTPS id kd13sor1298229ejc.56.2021.04.09.05.35.43
        for <sxxxx.cxxxx@gmail.com>
        (Google Transport Security);
        Fri, 09 Apr 2021 05:35:43 -0700 (PDT)
Received-SPF: pass (google.com: domain of fxxxxxxxxxx@gmail.com designates 209.85.220.41 as permitted sender) client-ip=209.85.220.41;
Authentication-Results: mx.google.com;
       dkim=pass header.i=@gmail.com header.s=20161025 header.b=e72Bz8nw;
       spf=pass (google.com: domain of fxxxxxxxxxx@gmail.com designates 209.85.220.41 as permitted sender) smtp.mailfrom=fxxxxxxxxxx@gmail.com;
       dmarc=pass (p=NONE sp=QUARANTINE dis=NONE) header.from=gmail.com
DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed;
        d=gmail.com; s=20161025;
        h=from:to:subject:date:message-id:mime-version:thread-index
         :content-language;
        bh=pdk79xbDyHvYq5L6e08DBSeYp6uMJLfGyugTatCUinQ=;
        b=e72Bz8nwG1S4yYOc625u0Mq8j+ATEJTHxgKwtqOjp8xjtGrlOgxBHVpt0MfCj78/6u
         U5y7Fb0sWfd9lzgtRYHDBeASiZnLU8Vc8jUyE85Fv6kebxIVN3bJuZTSUEqIf4367znG
         lDbPqeXOoeChCBylZfr7XudBhB5DLPm17DCIOhCJFFrJD9ZMjfnFhnGFc4oAds/U9cvG
         BVOC4gLCfYxG6Gsjkfx0dCIgnxtoG2N9hQaZZPB9lgGTeSCHnkH3D0LI7sYQNEPvRhCU
         +R7Cf+Cwa5MDZukuLXAq04x6CMG3/ASB/ihtb3/Kj0LgrKRMulc5CDwirLQZbbvr1LiG
         AgZA==
X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed;
        d=1e100.net; s=20161025;
        h=x-gm-message-state:from:to:subject:date:message-id:mime-version
         :thread-index:content-language;
        bh=pdk79xbDyHvYq5L6e08DBSeYp6uMJLfGyugTatCUinQ=;
        b=YwEA1rMs2NbGjr17edNHiCTRB5XdqSg7x3xFZSZaZK3jsw87hC7lzRpwtjhr+cq3gJ
         8M45k9tAmkr4yIkwOOeFxhZvyXKWTYaXB4/Ux7S0e7vBhUYcd6VlRGQ1o4lzmDWBJqqD
         ceRz+EhYmXg3yWyA261tNKV2xUdLb0FVojmYksvYOqXz9F3JJ90PJJL07VoYlBn5tMv3
         3DSWN7W+BrtfgUU0LhwY1Y+GNzCiPBAdIlLnvufYr05mZD+njHpvAcDyIzuf4W0zWXZU
         286jOb7aSIQt2MaCIguOWJaji2Qd2cl19LHiHPehwT7RoDOdMRnKZEMICM9PdLZ9B213
         MEiQ==
X-Gm-Message-State: AOAM530YVoAxC68mmNqDwp+8TpqImZEdwfkvE79L7PLyRawJHrolB35y 3wDV1AT1Pf99ST72QRufacU=
X-Google-Smtp-Source: ABdhPJxnWDb6KHNboUpTbvJb+J1EX/Afmew0nSXvxB6cyjV7H6eHvi8pLu1NcafdqLd1XBN4PUXBZA==
X-Received: by 2002:a17:906:1c05:: with SMTP id k5mr15682006ejg.456.1617971743359;
        Fri, 09 Apr 2021 05:35:43 -0700 (PDT)
Return-Path: <fxxxxxxxxxx@gmail.com>
Received: from DESKTOP7K26SNF (102-65-13-79.ftth.web.africa. (102.65.13.79))
        by smtp.gmail.com with ESMTPSA id ml13sm723340ejb.7.2021.04.09.05.35.41
        (version=TLS1_2 cipher=ECDHE-ECDSA-AES128-GCM-SHA256 bits=128/128);
        Fri, 09 Apr 2021 05:35:42 -0700 (PDT)
From: <fxxxxxxxxxx@gmail.com>
To: <txxxxx@mweb.co.za>
Subject: Photographic Club
Date: Fri, 9 Apr 2021 14:35:40 +0200
Message-ID: <039801d72d3c$db232440$91696cc0$@gmail.com>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary="----=_NextPart_000_0399_01D72D4D.9EAD7AE0"
X-Mailer: Microsoft Outlook 16.0
Thread-Index: AdctO/QbXbAiuYUgRcSHQ5sy4Vd0DA==
Content-Language: en-za
X-Antivirus: Avast (VPS 210408-4, 04/08/2021), Outbound message
X-Antivirus-Status: Clean

query – SQL Analyze – dbms_stats consuming much CPU on Oracle Server

In one bigger DB with many user schemas and big tables I have the devs starting regulary the Analyze select dbms_stats queries , that consume a lot of cpu when started for many users at once. These analyze queries have sometimes over 2-3 Minutes duration time and all of them have COUNT inside and the explain plan shows that the queries use every time table access FULL scan.

/* SQL Analyze(0) */ select /*+  full(t)    parallel(t,5) parallel_index(t,5) dbms_stats

A lot of those queries need to collect statistics, but during this period they consume all of the server CPUs, and I would like to see if they can be optimized.
The queries are similar like in the Doc ID 2552730.1

They have a lot of repetitve substrb(dump(max( and to_char(count( sub-functions for the table columns.

PX Coordinator is starting them parallel, which is ok, before SORT aggregate and after sort agreggate in the explain plan.
Many tables have over 150 million rows.

At the end of the queries we have also TOPN,NIL,NDV methods repeating many times.

Have you maybe encountered same issues and which approach could be taken to optimize those queries if possible. SQL Advisor gave back no recommendations.

Tool to analyze frequency of purchases

Hi!

Does anyone know or use a tool to analyze a frequency of purchases? For example:

Case 1

‘Client A’ had bought a ‘Product B’ 1st March and it was his 1st purchase ever. Then 1st April a ‘Client A’ made another (2nd) purchase and bought a ‘Product C’.

I would like to measure/check:

  1. Period of time between 1st and 2nd purchase
  2. What is the most popular product buying as a 2nd if 1st purchase was a ‘Product B’?

Case 2

‘Client A’ bought at least 2 items during 1st purchase. A ‘Product B’ and a ‘Product C’.

I would like to measure/check:

  1. What is the most frequently buying product in pair with a ‘Product B’

Platform : PrestaShop
SEMrush

Thanks in advance for your responses

 

how can I analyze my website's source code?

Hi! I think there is a destructive code in my website's source code. how can I analyze it? Is there any tools?

How to set up a recurrence relation to analyze number of execution of the basic operation of this algorithm?

This an algorithm to count inversions in an array, this is a divide and conquer algorithm, I want to know what is the basic operation of the this algorithm and how do I set up a recurrence relation to analyze number of execution of the basic step?

The definition of basic step: The operation contributing the most to the total running time of an algorithm.
– It is typically the most time consuming operation in the algorithm’s innermost loop.
• Examples: Key comparison operation; arithmetic operation (division being
the most time-consuming, followed by multiplication)

this is the algorithm

  public static int merge(int() arr, int() aux, int low, int mid, int high)
    {
        int k = low, i = low, j = mid + 1;
        int inversionCount = 0;
 
        // while there are elements in the left and right runs
        while (i <= mid && j <= high)
        {
            if (arr(i) <= arr(j)) {
                aux(k++) = arr(i++);
            }
            else {
                aux(k++) = arr(j++);
                inversionCount += (mid - i + 1);    // NOTE
            }
        }
 
        // copy remaining elements
        while (i <= mid) {
            aux(k++) = arr(i++);
        }
 
        // no need to copy the second half
 
        // copy back to the original array to reflect sorted order
        for (i = low; i <= high; i++) {
            arr(i) = aux(i);
        }
 
        return inversionCount;
    }
 
    // Sort array `arr(low…high)` using auxiliary array `aux`
    public static int mergeSort(int() arr, int() aux, int low, int high)
    {
        // Base case
        if (high == low) {    // if run size == 1
            return 0;
        }
 
        // find midpoint
        int mid = (low + ((high - low) >> 1));
        int inversionCount = 0;
 
        // recursively split runs into two halves until run size == 1,
        // then merges them and return up the call chain
 
        // split/merge left half
        inversionCount += mergeSort(arr, aux, low, mid);
 
        // split/merge right half
        inversionCount += mergeSort(arr, aux, mid + 1, high);
 
        // merge the two half runs
        inversionCount += merge(arr, aux, low, mid, high);
 
        return inversionCount;
    }

how do I set up a recurrence relation to analyze number of execution of the basic operation? Please also provide explanation!!

ux designer – Can we use A/B testing for analyze new features?

Hello I’m quite newbie in UX, especially in A/B Testing methods.

In my opinion and after I read some of articles. A/B testing usually used for analyze some new call to action button, copywriting, layout, or colors. Measure the new and existing design with conversion rate, etc.

But the question is, can A/B testing used for analyze new features?
For the example I have 2 variation of design. existing and new design. I want to implement new features in new design. So, I doing A/B testing for monitoring the conversion rate of:

  • Existing design (without new feature).
  • New design (with new feature).

Is it possible to find a winner of that variations? Can we conclude that our new feature have a positive response for users?

do you use any tools to analyze or monitor your competitor ?

Hi,

do you use any tools to analyze or monitor your competitor ?

it may include their backlnk,seo,ad,…etc …. | Read the rest of https://www.webhostingtalk.com/showthread.php?t=1837317&goto=newpost

replication – Is there a way to analyze a MySQL query and determine whether it’s read-only?

I have a main database and a replica that is automatically kept in sync with the main one. It would be nice, for each query I make, to perform all data- and database-altering queries on the main database, and all read-only queries on the replica. I’m envisioning some kind of query analyzer, and then based on its output, using the correct database, but maybe there’s a different way to do that that I’m not aware of.

postgresql – When autovaccum will analyze?

Let’s suppose that a table foo became eligible for autovacuum analyze, e.g. I have inserted a number of rows into foo that exceeds autovacuum_analyze_scale_factor * number of rows + autovacuum_analyze_threshold effective threshold. I can’t figure out which are the conditions that should be satisfied in order to have autovacuum performing the analyze on foo.

Will autovacuum analyze run for table foo only if there are no transactions? Or it can run even during active transactions with the conditions that: (1) no transaction is reading a previous version of table foo and (2) the autovacuum analyze can gain SHARE UPDATE EXCLUSIVE lock on table foo?

These questions are related to particular case. I peform a significant number of INSERTs into foo in one transaction and then some UPDATEs on foo in a second transaction. I need the autovacuum analyze to run before the 2nd transaction in order to have an up to date statistics of foo for my query planner better estimates. Are there a way to guarantee that the autovacuum analyze will run before the 2nd transaction? Maybe to sleep (I’m running both transactions from Java app) couple of milliseconds between transactions?